To see the other types of publications on this topic, follow the link: Computer Optimization of Parameters.
Dissertations / Theses on the topic 'Computer Optimization of Parameters'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 dissertations / theses for your research on the topic 'Computer Optimization of Parameters.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse dissertations / theses on a wide variety of disciplines and organise your bibliography correctly.
1
Naber, John F. "The optimization of SPICE modeling parameters utilizing the Taguchi methodology." Diss., Virginia Tech, 1992. http://hdl.handle.net/10919/38542.
Full textAbstract:
A new optimization technique for SPICE modeling parameters has been developed in this dissertation to increase the accuracy of the
circuit simulation. The importance of having accurate circuit simulation models is to prevent the very costly redesign of an
Integrated Circuit (IC). This radically new optimization technique utilizes the Taguchi method to improve the fit between measured and
simulated I-V curves for GaAs MESFETs. The Taguchi method consists of developing a Signal-to-Noise Ratio (SNR) equation that will find the optimum combination of controllable signal levels in a design or process to make it robust or as insensitive to noise as
possible. In this dissertation, the control factors are considered the circuit model curve fitting parameters and the noise is
considered the variation in the simulated I-V curves from the measured I-V curves. This is the first known application of the
Taguchi method to the optimization of IC curve fitting model parameters. In addition, this method is not technology or device dependent and can be applied to silicon devices as well. Improvements in the accuracy of the simulated I-V curve fit reaching 80% has been achieved between DC test extracted parameters and the Taguchi optimized parameters. Moreover, the computer CPU execution time of the optimization process is 96% less than a commercial optimizer utilizing the Levenberg-Marquardt algorithm (optimizing 31 FETs). This technique does a least square fit on the data comparing measured currents versus simulated currents for various combinations of SPICE parameters. The mean and standard deviation of this least squares fit is incorporated in determining the SNR, providing the best combination of parameters within the evaluated range. Furthermore, the optimum values of the parameters are found without additional simulation by fitting the response curves to a quadratic equation and finding the local maximum. This technique can easily be implemented with any simulator that utilizes simulation modeling parameters extracted from measured DC test data. In addition, two methods are evaluated to obtain the worst case modeling parameters. One method lobks at the correlation coefficients between modeling parameters and the second looks at the actual device parameters that define the +/- 30 limits of the process. Lastly, an example is given that describes the applicability of the Taguchi methodology in the design of a differential amplifier, that accounts for the effect of offset voltage.Ph. D.
2
Pethe, Shirish A. "Optimization of process parameters for reduced thickness CIGSeS thin film solar cells." Doctoral diss., University of Central Florida, 2010. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4623.
Full textAbstract:
With the advent of the 21st century, one of the serious problems facing mankind is harmful effects of global warming. Add to that the ever increasing cost of fuel and the importance of development of clean energy resources as alternative to fossil fuel has becomes one of the prime and pressing challenges for modern science and technology in the 21st century. Recent studies have shown that energy related sources account for 50% of the total emission of carbon dioxide in the atmosphere. All research activities are focused on developing various technologies that are capable of converting sunlight into electricity with high efficiency and can be produced using a cost-effective process. One of such technologies is the CuIn[sub1-x]Ga[subx]Se[sub2] (CIGS) and its alloys that can be produced using cost-effective techniques and also exhibit high photo-conversion efficiency. The work presented here discusses some of the fundamental issues related to high volume production of CIGS thin film solar cells. Three principal issues that have been addressed in this work are effect of reduction in absorber thickness on device performance, micrononuniformity involved with amount of sodium and its effect on device performance and lastly the effect of working distance on the properties of molybdenum back contact. An effort has been made to understand the effect of absorber thickness on PV parameters and optimize the process parameters accordingly. Very thin (<1 [micro]m) absorber film were prepared by selenization using metallorganic selenium source in a conventional furnace and by RTP using Se vapor. Sulfurization was carried out using H2S gas. Devices with efficiencies reaching 9% were prepared for very thin (<1 [micro]m) CIGS and CIGSeS thin films. It was shown through this work that the absorber thickness reduction of 64% results in the efficiency drop of only 32%. With further optimization of the reaction process of the absorber layer as well as the other layers higher efficiencies can be achieved. The effect of sodium on the device performance is experimentally verified in this work. To the best of our knowledge the detrimental effect of excess sodium has been verified by experimental data and effort has been made to correlate the variation in PV parameter to theoretical models of effect of sodium. It has been a regular practice to deposit thin barrier layer prior to molybdenum deposition to reduce the micrononuniformities caused due to nonuniform out diffusion of sodium from the soda lime glass. However, it was proven in this work that an optimally thick barrier layer is necessary to reduce the out diffusion of sodium to negligible quantities and thus reduce the micrononuniformities. Molybdenum back contact deposition is a bottleneck in high volume manufacturing due to the current state of art where multi layer molybdenum film needs to be deposited to achieve the required properties. In order to understand and solve this problem experiments were carried out. The effect of working distance (distance between the target and the substrate) on film properties was studied and is presented in this work. During the course of this work efforts were taken to carry out a systematic and detailed study of some of the fundamental issues related to CIGS technology and particular for high volume manufacturing of CIGS PV modules and lay a good foundation for further improvement of PV performance of CIGS thin film solar cells prepared by the two step process of selenization and sulfurization of sputtered metallic precursors.ID: 030423396; System requirements: World Wide Web browser and PDF reader.; Mode of access: World Wide Web.; Thesis (Ph.D.)--University of Central Florida, 2010.; Includes bibliographical references (p. 108-116).
Ph.D.
Doctorate
Department of Electrical Engineering and Computer Science
Engineering and Computer Science
3
Panis, Renato P. "Robust parameter optimization strategies in computer simulation experiments." Diss., This resource online, 1994. http://scholar.lib.vt.edu/theses/available/etd-06062008-164719/.
Full text
4
Lavesson, Niklas. "Evaluation of classifier performance and the impact of learning algorithm parameters." Thesis, Blekinge Tekniska Högskola, Institutionen för programvaruteknik och datavetenskap, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-4578.
Full textAbstract:
Much research has been done in the fields of classifier performance evaluation and optimization. This work summarizes this research and tries to answer the question if algorithm parameter tuning has more impact on performance than the choice of algorithm. An alternative way of evaluation; a measure function is also demonstrated. This type of evaluation is compared with one of the most accepted methods; the cross-validation test. Experiments, described in this work, show that parameter tuning often has more impact on performance than the actual choice of algorithm and that the measure function could be a complement or an alternative to the standard cross-validation tests.
5
Argyn, Aidar. "Material And Heat Balance Calculations Of Eti-bakir Plant By Computer." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/2/12609734/index.pdf.
Full textAbstract:
In this study the data taken from Outokumpu type Flash smelter of Eti-Bakir Plant (Samsun, Turkey) was used to write a computer program in Visual Basic with interface to Excel. Flash smelting is the pyrometallurgical process for smelting metal sulfide concentrates, used in Eti-Bakir plant. In this plant, copper flash smelting consists of blowing fine, dried copper sulfide concentrate mixtures, silica flux, lignite with air into the furnace and natural gas as main fuel. The molten matte is the principal product of the furnace and slag contains 0.5-2% Cu. It is sent to a slag treatment (flotation) process for Cu recovery. This flash furnace off-gas contains from 8-12 volume % SO2 which is fixed as H2SO4. Written program was used to optimize the consumption of oxygen enriched air, fuel and lignite in this Flash Smelter by making material and heat balance of the plant.
6
Kaul, Ashwani. "Optimization of Process Parameters for Faster Deposition of CuIn1-xGaxS2 and CuIn1-xGaxSe2-ySy Thin Film Solar Cells." Doctoral diss., University of Central Florida, 2012. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5336.
Full textAbstract:
Thin film solar cells have the potential to be an important contributor to the world energy demand in the 21st century. Among all the thin film technologies, CuInGaSe2 (CIGS) thin film solar cells have achieved the highest efficiency. However, the high price of photovoltaic (PV) modules has been a major factor impeding their growth for terrestrial applications. Reduction in cost of PV modules can be realized by several ways including choosing scalable processes amenable to large area deposition, reduction in the materials consumption of active layers, and attaining faster deposition rates suitable for in-line processing. Selenization-sulfurization of sputtered metallic Cu-In-Ga precursors is known to be more amenable to large area deposition. Sputter-deposited molybdenum thin film is commonly employed as a back contact layer for CIGS solar cells. However, there are several difficulties in fabricating an optimum back contact layer. It is known that molybdenum thin films deposited at higher sputtering power and lower gas pressure exhibit better electrical conductivity. However, such films exhibit poor adhesion to the soda-lime glass substrate. On the other hand, films deposited at lower discharge power and higher pressure although exhibit excellent adhesion show lower electrical conductivity. Therefore, a multilayer structure is normally used so as to get best from the two deposition regimes. A multi-pass processing is not desirable in high volume production because it prolongs total production time and correspondingly increases the manufacturing cost. In order to make manufacturing compliant with an in-line deposition, it is justifiable having fewer deposition sequences. Thorough analysis of pressure and power relationship of film properties deposited at various parameters has been carried out. It has been shown that it is possible to achieve a molybdenum back contact of desired properties in a single deposition pass by choosing the optimum deposition parameters. It is also shown that the film deposited in a single pass is actually a composite structure. CIGS solar cells have successfully been completed on the developed single layer back contact with National Renewable Energy Laboratory (NREL) certified device efficiencies >11%. The optimization of parameters has been carried out in such a way that the deposition of back contact and metallic precursors can be carried out in identical pressure conditions which is essential for in-line deposition without a need for load-lock. It is know that the presence of sodium plays a very critical role during the growth of CIGS absorber layer and is beneficial for the optimum device performance. The effect of sodium location during the growth of the absorber layer has been studied so as to optimize its quantity and location in order to get devices with improved performance. NREL certified devices with efficiencies >12% have been successfully completed.Ph.D.
Doctorate
Materials Science Engineering
Engineering and Computer Science
Materials Science and Engineering
7
Lee, Sang Heon. "Efficient design and optimization of robust parameter experiments." Diss., Georgia Institute of Technology, 1991. http://hdl.handle.net/1853/24328.
Full text
8
Chen, Zhaozhong. "Visual-Inertial SLAM Extrinsic Parameter Calibration Based on Bayesian Optimization." Thesis, University of Colorado at Boulder, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=10789260.
Full textAbstract:
VI-SLAM (Visual-Inertial Simultaneous Localization and Mapping) is a popular way for robotics navigation and tracking. With the help of sensor fusion from IMU and camera, VI-SLAM can give a more accurate solution for navigation. One important problem needs to be solved in VI-SLAM is that we need to know accurate relative position between camera and IMU, we call it the extrinsic parameter. However, our measurement of the rotation and translation between IMU and camera is noisy. If the measurement is slightly o?, the result of SLAM system will be much more away from the ground truth after a long run. Optimization is necessary. This paper uses a global optimization method called Bayesian Optimization to optimize the relative pose between IMU and camera based on the sliding window residual output from VISLAM. The advantage of using Bayesian Optimization is that we can get an accurate pose estimation between IMU and camera from a large searching range. Whats more, thanks to the Gaussian Process or T process of Bayesian Optimization, we can get a result with a known uncertainty, which cannot be done by many optimization solutions.
9
Lakkimsetti, Praveen Kumar. "A framework for automatic optimization of MapReduce programs based on job parameter configurations." Kansas State University, 2011. http://hdl.handle.net/2097/12011.
Full textAbstract:
Master of ScienceDepartment of Computing and Information Sciences
Mitchell L. Neilsen
Recently, cost-effective and timely processing of large datasets has been playing an important role in the success of many enterprises and the scientific computing community. Two promising trends ensure that applications will be able to deal with ever increasing data volumes: first, the emergence of cloud computing, which provides transparent access to a large number of processing, storage and networking resources; and second, the development of the MapReduce programming model, which provides a high-level abstraction for data-intensive computing. MapReduce has been widely used for large-scale data analysis in the Cloud [5]. The system is well recognized for its elastic scalability and fine-grained fault tolerance. However, even to run a single program in a MapReduce framework, a number of tuning parameters have to be set by users or system administrators to increase the efficiency of the program. Users often run into performance problems because they are unaware of how to set these parameters, or because they don't even know that these parameters exist. With MapReduce being a relatively new technology, it is not easy to find qualified administrators [4]. The major objective of this project is to provide a framework that optimizes MapReduce programs that run on large datasets. This is done by executing the MapReduce program on a part of the dataset using stored parameter combinations and setting the program with the most efficient combination and this modified program can be executed over the different datasets. We know that many MapReduce programs are used over and over again in applications like daily weather analysis, log analysis, daily report generation etc. So, once the parameter combination is set, it can be used on a number of data sets efficiently. This feature can go a long way towards improving the productivity of users who lack the skills to optimize programs themselves due to lack of familiarity with MapReduce or with the data being processed.
10
Gembler, Felix [Verfasser]. "Parameter Optimization for Brain-Computer Interfaces based on Visual Evoked Potentials / Felix Gembler." Bielefeld : Universitätsbibliothek Bielefeld, 2020. http://d-nb.info/1222672227/34.
Full text
11
Sanders, Samantha Corinne. "Informing the use of Hyper-Parameter Optimization Through Meta-Learning." BYU ScholarsArchive, 2017. https://scholarsarchive.byu.edu/etd/6392.
Full textAbstract:
One of the challenges of data mining is finding hyper-parameters for a learning algorithm that will produce the best model for a given dataset. Hyper-parameter optimization automates this process, but it can still take significant time. It has been found that hyperparameter optimization does not always result in induced models with significant improvement over default hyper-parameters, yet no systematic analysis of the role of hyper-parameter optimization in machine learning has been conducted. We propose the use of meta-learning to inform the decision to optimize hyper-parameters based on whether default hyper-parameter performance can be surpassed in a given amount of time. We will build a base of metaknowledge, through a series of experiments, to build predictive models that will assist in the decision process.
12
Busuioc, Dan. "Circuit Model Parameter Extraction and Optimization for Microwave Filters." Thesis, University of Waterloo, 2002. http://hdl.handle.net/10012/804.
Full textAbstract:
This thesis presents a method for parameter extraction of circuit elements from microwave filters. This diagnosis method can be applied to a sufficiently large number of filters and it can also be used in conjunction with a neural network model for filter design, greatly reducing development time. This thesis is an introduction of parameter extraction and circuit modelling through use of neural networks. It also presents an implementation of the proposed method as well as numerical results and validation data. Detailed implementation code is presented in the appendix.
13
Engström, Messén Matilda, and Elvira Moser. "Pre-planning of Individualized Ankle Implants Based on Computed Tomography - Automated Segmentation and Optimization of Acquisition Parameters." Thesis, KTH, Fysik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-297674.
Full textAbstract:
The structure of the ankle joint complex creates an ideal balance between mobility and stability, which enables gait. If a lesion emerges in the ankle joint complex, the anatomical structure is altered, which may disturb mobility and stability and cause intense pain. A lesion in the articular cartilage on the talus bone, or a lesion in the subchondral bone of the talar dome, is referred to as an Osteochondral Lesion of the Talus (OLT). Replacing the damaged cartilage or bone with an implant is one of the methods that can be applied to treat OLTs. Episurf Medical develops and produces patient-specific implants (Episealers) along with the necessary associated surgical instruments by, inter alia, creating a corresponding 3D model of the ankle (talus, tibial, and fibula bones) based on either a Magnetic Resonance Imaging (MRI) scan or a Computed Tomography (CT) scan. Presently, the3D models based on MRI scans can be created automatically, but the 3Dmodels based on CT scans must be created manually, which can be very time-demanding. In this thesis project, a U-net based Convolutional Neural Network (CNN) was trained to automatically segment 3D models of ankles based on CT images. Furthermore, in order to optimize the quality of the incoming CT images, this thesis project also consisted of an evaluation of the specified parameters in the Episurf CT talus protocol that is being sent out to the clinics. The performance of the CNN was evaluated using the Dice Coefficient (DC) with five-fold cross-validation. The CNN achieved a mean DC of 0.978±0.009 for the talus bone, 0.779±0.174 for the tibial bone, and 0.938±0.091 for the fibula bone. The values for the talus and fibula bones were satisfactory and comparable to results presented in previous researches; however, due to background artefacts in the images, the DC achieved by the network for the segmentation of the tibial bone was lower than the results presented in previous researches. To correct this, a noise-reducing filter will be implemented.Fotledens komplexa anatomi ger upphov till en ideal balans mellan rörlighetoch stabilitet, vilket i sin tur möjliggör gång. Fotledens anatomi förändras när en skada uppstår, vilket kan påverka rörligheten och stabiliteten samt orsaka intensiv smärta. En skada i talusbenets ledbrosk eller i det subkondrala benet på talusdomen benämns som en Osteochondral Lesion of the Talus(OLT). En metod att behandla OLTs är att ersätta den del brosk eller bensom är skadat med ett implantat. Episurf Medical utvecklar och producerar individanpassade implantat (Episealers) och tillhörande nödvändiga kirurgiska instrument genom att, bland annat, skapa en motsvarande 3D-modell av fotleden (talus-, tibia- och fibula-benen) baserat på en skanning med antingen magnetisk resonanstomografi (MRI) eller datortomografi (CT). I dagsläget kan de 3D-modeller som baseras på MRI-skanningar skapas automatiskt, medan de 3D-modeller som baseras på CT-skanningar måste skapas manuellt - det senare ofta tidskrävande. I detta examensarbete har ett U-net-baserat Convolutional Neuralt Nätverk (CNN) tränats för att automatiskt kunna segmentera 3D-modeller av fotleder baserat på CT-bilder. Vidare har de speciferade parametrarna i Episurfs CT-protokoll för fotleden som skickas ut till klinikerna utvärderats, detta för att optimera bildkvaliteten på de CT-bilder som används för implantatspositionering och design. Det tränade nätverkets prestanda utvärderades med hjälp av Dicekoefficienten (DC) med en fem-delad korsvalidering. Nätverket åstadkom engenomsnittlig DC på 0.978±0.009 för talusbenet, 0.779±0.174 för tibiabenet, och 0.938±0.091 för fibulabenet. Värdena för talus och fibula var adekvata och jämförbara med resultaten presenterade i tidigare forskning. På grund av bakgrundsartefakter i bilderna blev den DC som nätverket åstadkom för sin segmentering av tibiabenet lägre än tidigiare forskningsresultat. För att korrigera för bakgrundsartefakterna kommer ett brusreduceringsfilter implementeras
14
Granados, Murillo Adrian. "A genetic algorithm for network transport protocol parameter optimization." [Pensacola, Fla.] : University of West Florida, 2009. http://purl.fcla.edu/fcla/etd/WFE0000176.
Full textAbstract:
Thesis (M.S.)--University of West Florida, 2009.Submitted to the Dept. of Computer Science. Title from title page of source document. Document formatted into pages; contains 66 pages. Includes bibliographical references.
15
Chakradhar, Vineel A. "Evaluating parameter optimization in locality-sensitive hashing for high-dimensional physiological waveforms." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/120650.
Full textAbstract:
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.Cataloged from PDF version of thesis. "The pagination listed in the Table of Contents does not correlate with actual page numbering"--Disclaimer Notice page.
Includes bibliographical references (pages 71-72).
We develop and evaluate a theoretical architecture to inform parameter choice for locality-sensitive hashing methods used towards identifying similarity in physiological waveform time-series data. The goal is to achieve increased probability of successful patient outcomes in emergency rooms by tackling the problem of efficient information retrieval within massive, high-dimensional medical datasets. To solve this problem, we explore the relationship between a number of data inputs and elements of locality-sensitive hashing schemes in order to drive optimal choice of parameters throughout the pipeline from raw data to locality-sensitive hashing output. We achieve significant increases in retrieval times while generally maintaining the prediction accuracy achieved by naive retrieval methodologies.
by Vineel A. Chakradhar.
M. Eng.
16
Jonah, Olutola. "Optimization of Wireless Power Transfer via Magnetic Resonance in Different Media." FIU Digital Commons, 2013. http://digitalcommons.fiu.edu/etd/876.
Full textAbstract:
A wide range of non-destructive testing (NDT) methods for the monitoring the health of concrete structure has been studied for several years. The recent rapid evolution of wireless sensor network (WSN) technologies has resulted in the development of sensing elements that can be embedded in concrete, to monitor the health of infrastructure, collect and report valuable related data. The monitoring system can potentially decrease the high installation time and reduce maintenance cost associated with wired monitoring systems. The monitoring sensors need to operate for a long period of time, but sensors batteries have a finite life span. Hence, novel wireless powering methods must be devised.
The optimization of wireless power transfer via Strongly Coupled Magnetic Resonance (SCMR) to sensors embedded in concrete is studied here. First, we analytically derive the optimal geometric parameters for transmission of power in the air. This specifically leads to the identification of the local and global optimization parameters and conditions, it was validated through electromagnetic simulations. Second, the optimum conditions were employed in the model for propagation of energy through plain and reinforced concrete at different humidity conditions, and frequencies with extended Debye's model. This analysis leads to the conclusion that SCMR can be used to efficiently power sensors in plain and reinforced concrete at different humidity levels and depth, also validated through electromagnetic simulations.
The optimization of wireless power transmission via SMCR to Wearable and Implantable Medical Device (WIMD) are also explored. The optimum conditions from the analytics were used in the model for propagation of energy through different human tissues. This analysis shows that SCMR can be used to efficiently transfer power to sensors in human tissue without overheating through electromagnetic simulations, as excessive power might result in overheating of the tissue.
Standard SCMR is sensitive to misalignment; both 2-loops and 3-loops SCMR with misalignment-insensitive performances are presented. The power transfer efficiencies above 50% was achieved over the complete misalignment range of 0°-90° and dramatically better than typical SCMR with efficiencies less than 10% in extreme misalignment topologies.
17
Reiling, Anthony J. "Convolutional Neural Network Optimization Using Genetic Algorithms." University of Dayton / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1512662981172387.
Full text
18
Yin, Emmy, and Klas Wijk. "Bayesian Parameter Tuning of the Ant Colony Optimization Algorithm : Applied to the Asymmetric Traveling Salesman Problem." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-302801.
Full textAbstract:
The parameter settings are vital for meta-heuristics to be able to approximate the problems they are applied to. Good parameter settings are difficult to find as there are no general rules for finding them. Hence, they are often manually selected, which is seldom feasible and can give results far from optimal. This study investigated the potential of tuning meta-heuristics using a hyper- parameter tuning algorithm from the field of machine learning, where parameter tuning is a common and well-explored area. We used Bayesian Optimization, a state-of-the-art black-box optimization method, to tune the Ant Colony Optimization meta-heuristic. Bayesian Optimization using the three different acquisition functions Expected Improvement, Probability of Improvement and Lower Confidence Bound, as well as the three functions combined using softmax, were evaluated and compared to using Random Search as an optimization method. The Ant Colony Optimization algorithm with its parameters tuned by the different methods was applied to four Asymmetric Traveling Salesman problem instances. The results showed that Bayesian Optimization both leads to better solutions and does so in significantly fewer iterations than Random Search. This suggests that Bayesian Optimization is preferred to Random Search as an optimization method for the Ant Colony Optimization metaheuristic, opening for further research in tuning meta-heuristics with Bayesian Optimization.Bra val av parametrar är avgörande för hur väl meta-heuristiker lyckas approximera problemen de tillämpas på. Detta kan emellertid vara svårt eftersom det inte finns några generella riktlinjer för hur de ska väljas. Det gör att parametrar ofta ställs in manuellt, vilket inte alltid är genomförbart och dessutom kan leda till resultat långt från det optimala. Att ställa in hyperparametrar är dock ett välutforskat problem inom maskininlärning. Denna studie undersöker därför möjligheten att använda algoritmer från maskininlärningsområdet för att ställa in parametrarna på meta-heurstiker. Vi använde Bayesiansk optimering, en modern optimeringsmetod för optimering av okända underliggande funktioner, på meta-heuristiken myrkolonioptimering. Bayesiansk optimering med förvärvsfunktionerna förväntad förbättring, sannolikhet för förbättring och undre förtroendegräns, samt alla tre kombinerade med softmax, utvärderades och jämfördes med slumpmässig sökning som en optimeringsmetod. Myrkolonioptimering vars parametrar ställts in med de olika metoderna tillämpades på fyra instanser av det asymmetriska handlesresandeproblemet. Resultaten visade på att Bayesiansk optimering leder till bättre approximeringar, som kräver signifikant färre iterationer att hitta jämfört med slumpmässig sökning. Detta indikerar att Bayesiansk optimering är att föredra framför slumpmässig sökning, och öppnar för fortsatt forskning av Bayesiansk optimering av metaheuristiker.
19
DiMascio, Michelle Augustine. "Convolutional Neural Network Optimization for Homography Estimation." University of Dayton / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1544214038882564.
Full text
20
Hogan, Erik A. "An efficient method for the optimization of viscoplastic constitutive model constants." Honors in the Major Thesis, University of Central Florida, 2009. http://digital.library.ucf.edu/cdm/ref/collection/ETH/id/1274.
Full textAbstract:
This item is only available in print in the UCF Libraries. If this is your Honors Thesis, you can help us make it available online for use by researchers around the world by following the instructions on the distribution consent form at http://library.ucf.edu/Systems/DigitalInitiatives/DigitalCollections/InternetDistributionConsentAgreementForm.pdf You may also contact the project coordinator, Kerri Bottorff, at kerri.bottorff@ucf.edu for more information.Bachelors
Engineering and Computer Science
Aerospace Engineering
21
Morcos, Karim M. "Genetic network parameter estimation using single and multi-objective particle swarm optimization." Thesis, Kansas State University, 2011. http://hdl.handle.net/2097/9207.
Full textAbstract:
Master of ScienceDepartment of Electrical and Computer Engineering
Sanjoy Das
Stephen M. Welch
Multi-objective optimization problems deal with finding a set of candidate optimal solutions to be presented to the decision maker. In industry, this could be the problem of finding alternative car designs given the usually conflicting objectives of performance, safety, environmental friendliness, ease of maintenance, price among others. Despite the significance of this problem, most of the non-evolutionary algorithms which are widely used cannot find a set of diverse and nearly optimal solutions due to the huge size of the search space. At the same time, the solution set produced by most of the currently used evolutionary algorithms lacks diversity. The present study investigates a new optimization method to solve multi-objective problems based on the widely used swarm-intelligence approach, Particle Swarm Optimization (PSO). Compared to other approaches, the proposed algorithm converges relatively fast while maintaining a diverse set of solutions. The investigated algorithm, Partially Informed Fuzzy-Dominance (PIFD) based PSO uses a dynamic network topology and fuzzy dominance to guide the swarm of dominated solutions. The proposed algorithm in this study has been tested on four benchmark problems and other real-world applications to ensure proper functionality and assess overall performance. The multi-objective gene regulatory network (GRN) problem entails the minimization of the coefficient of variation of modified photothermal units (MPTUs) across multiple sites along with the total sum of similarity background between ecotypes. The results throughout the current research study show that the investigated algorithm attains outstanding performance regarding optimization aspects, and exhibits rapid convergence and diversity.
22
Lundberg, Martin. "Automatic parameter tuning in localization algorithms." Thesis, Linköpings universitet, Programvara och system, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-158132.
Full textAbstract:
Many algorithms today require a number of parameters to be set in order to perform well in a given application. The tuning of these parameters is often difficult and tedious to do manually, especially when the number of parameters is large. It is also unlikely that a human can find the best possible solution for difficult problems. To be able to automatically find good sets of parameters could both provide better results and save a lot of time. The prominent methods Bayesian optimization and Covariance Matrix Adaptation Evolution Strategy (CMA-ES) are evaluated for automatic parameter tuning in localization algorithms in this work. Both methods are evaluated using a localization algorithm on different datasets and compared in terms of computational time and the precision and recall of the final solutions. This study shows that it is feasible to automatically tune the parameters of localization algorithms using the evaluated methods. In all experiments performed in this work, Bayesian optimization was shown to make the biggest improvements early in the optimization but CMA-ES always passed it and proceeded to reach the best final solutions after some time. This study also shows that automatic parameter tuning is feasible even when using noisy real-world data collected from 3D cameras.
23
Bergkvist, Markus, and Tobias Olandersson. "Machine learning in simulated RoboCup." Thesis, Blekinge Tekniska Högskola, Institutionen för programvaruteknik och datavetenskap, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3827.
Full textAbstract:
An implementation of the Electric Field Approach applied to the simulated RoboCup is presented, together with a demonstration of a learning system. Results are presented from the optimization of the Electric Field parameters in a limited situation, using the learning system. Learning techniques used in contemporary RoboCup research are also described including a brief presentation of their results.
24
Cunningham, James. "Efficient, Parameter-Free Online Clustering." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1606762403895603.
Full text
25
Aribi, Noureddine. "Contribution à l'élicitation des paramètres en optimisation multicritère." Phd thesis, Université Nice Sophia Antipolis, 2014. http://tel.archives-ouvertes.fr/tel-01065629.
Full textAbstract:
De nombreuses méthodes existent pour résoudre des problèmes d'optimisation multicritère, et il n'est pas aisé de choisir une méthode suffisamment adaptée à un problème multicritère donné. En effet, après le choix d'une méthode multicritère, différents paramètres (e.g. poids, fonctions d'utilité, etc.) doivent être déterminés, soit pour trouver la solution optimale (meilleur compromis) ou pour classer l'ensemble des solutions faisables (alternatives). Justement, vue cette difficulté pour fixer les paramètres, les méthodes d'élicitation sont utilisées pour aider le décideur dans cette tâche de fixation des paramètres. Par ailleurs, nous supposons que nous disposons d'un ensemble de solutions plausibles, et nous faisons aussi l'hypothèse de la disponibilité au préalable, des informations préférentielles obtenues après une interaction avec le décideur. Dans la première contribution de ce travail, nous tirons profit d'une mesure statistique simple et rapidement calculable, à savoir, le coefficient de corrélation $rho$ de Spearman, afin de développer une approche gloutonne (approchée), et deux approches exactes basées sur la programmation par contraintes (PPC) et la programmation linéaire en nombres entiers (PLNE). Ces méthodes sont ensuite utilisées pour éliciter automatiquement les paramètres appropriés de la méthode multicritère basée sur l'ordre lexicographique. Nous proposons aussi des modèles d'élicitation des paramètres d'autres méthodes multicritère, telles que la méthode MinLeximax issue de la théorie du choix social et du partage équitable, la méthode de la somme pondérée et les opérateurs OWA.
26
Nilsson, Mikael. "Parameter Tuning Experiments of Population-based Algorithms." Thesis, Mittuniversitetet, Institutionen för informationsteknologi och medier, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-13836.
Full textAbstract:
In this study, three different algorithms are implemented to solve thecapacitated vehicle routing problem with and without time windows:ant colony optimization, a genetic algorithm and a genetic algorithmwith self-organizing map. For the capacitated vehicle routing problemthe Augerat et al’s benchmark problems were used and for the capaci-tated vehicle routing problem with time windows the Solomon’sbenchmark problems. All three algorithms were tuned over thirtyinstances per problem with the tuners SPOT and ParamILS. The tuningresults from all instances were combined to the final parameter valuesand tested on a larger set of instances. The test results were used tocompare the algorithms and tuners against each other. The ant colonyoptimization algorithm outperformed the other algorithms on bothproblems when considering all instances. The genetic algorithm withself-organizing map found more best known solutions than any otheralgorithm when using parameters, on the capacitated vehicle routingproblem. The algorithms performed well and several new best knownresults were discovered for the capacitated vehicle routing problem andnew best solutions found by heuristics were discovered for the 100customer Solomon problems. When comparing the tuners they bothworked well and no clear winner emerged.
27
Taylor, Graham. "Reinforcement Learning for Parameter Control of Image-Based Applications." Thesis, University of Waterloo, 2004. http://hdl.handle.net/10012/832.
Full textAbstract:
The significant amount of data contained in digital images present barriers to methods of learning from the information they hold. Noise and the subjectivity of image evaluation further complicate such automated processes. In this thesis, we examine a particular area in which these difficulties are experienced. We attempt to control the parameters of a multi-step algorithm that processes visual information. A framework for approaching the parameter selection problem using reinforcement learning agents is presented as the main contribution of this research. We focus on the generation of state and action space, as well as task-dependent reward. We first discuss the automatic determination of fuzzy membership functions as a specific case of the above problem. Entropy of a fuzzy event is used as a reinforcement signal. Membership functions representing brightness have been automatically generated for several images. The results show that the reinforcement learning approach is superior to an existing simulated annealing-based approach. The framework has also been evaluated by optimizing ten parameters of the text detection for semantic indexing algorithm proposed by Wolf et al. Image features are defined and extracted to construct the state space. Generalization to reduce the state space is performed with the fuzzy ARTMAP neural network, offering much faster learning than in the previous tabular implementation, despite a much larger state and action space. Difficulties in using a continuous action space are overcome by employing the DIRECT method for global optimization without derivatives. The chosen parameters are evaluated using metrics of recall and precision, and are shown to be superior to the parameters previously recommended. We further discuss the interplay between intermediate and terminal reinforcement.
28
Markgren, Hanna. "Fatigue analysis - system parameters optimization." Thesis, Umeå universitet, Institutionen för fysik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-151755.
Full textAbstract:
For a mechanical system exposed to repeated cyclic loads fatigue is one of the most common reasons for the system to fail. However fatigue failure calculations are not that well developed. Often when fatigue calculations are made they are done with standard loads and simplified cases. The fatigue life is the time from start of use until the system fails due to fatigue and there does exist some building blocks to calculate the fatigue life. The aim for this project was to put these building blocks together in a workflow that ca be used for calculations of the fatigue life. The workflow was built so that it should be easy to follow for any type of me- chanical system. The start of the workflow is the load history of the system. This is then converted into a stress history that is used for the calculations of the fatigue life. Finally the workflow was tested with two test cases to see if it was possible to use. In Algoryx Momentum the model for each case was set up and then the load history was extracted for each time step during the simulation. To convert the load history to stress history FEM calculations was needed, this was however not a part of this project so the constants to convert loads to stress was given. Then with the stress history in place it was possible to calculate the fatigue life. The results from both test cases were that it was possible to follow every step of the workflow and by this use the workflow to calculate the fatigue life. The second test also showed that with an optimization the system was improved and this resulted in a longer lifetime. To conclude the workflow seems to work as expected and is quite easy to follow. The result given by using the workflow shows the fatigue life, which was the target for the project. However, to be able to evaluate the workflow fully and understand how well the resluts can be trusted a comparison with empiric data would be needed. Still the results from the tests are that the workflow seem to give reasonable results when calculating fatigue life.
29
Samek, Michal. "Optimization of Aircraft Tracker Parameters." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2015. http://www.nusl.cz/ntk/nusl-234937.
Full textAbstract:
Diplomová práce se zabývá optimalizací systému pro sledování letadel, využívaného pro řízení letového provozu. Je popsána metodika vyhodnocování přesnosti sledovacího systému a přehled relevantních algoritmů pro sledování objektů. Dále jsou navrženy tři přístupy k řešení problému. První se pokouší identifikovat parametry filtrovacích algoritmů pomocí algoritmu Expectation-Maximisation, implementací metody maximální věrohodnosti. Druhý přístup je založen na prostých odhadech parametrů normálního rozložení z naměřených a referenčních dat. Nakonec je zkoumána možnost řešení pomocí optimalizačního algoritmu Evoluční strategie. Závěrečné vyhodnocení ukazuje, že třetí přístup je pro daný problém nejvhodnější.
30
Johansson, Christopher. "Optimization of wall parameters using CFD." Thesis, KTH, Aerodynamik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-159875.
Full textAbstract:
Computational Fluid Dynamics (CFD) is commonly used to calculate the pressure drop in systems with internal ow. To get accurate results the physics of the ow must be well dened together with the right material parameters of the considered geometry. The mate- rial parameter considered in this report is the wall roughness, or sand-grain roughness, and during the thesis work it has been investigated how dierent wall roughnesses aects the pressure drop. It has also been investigated how to set up a CFD simulation to accurately calculate the pressure drop. When setting up a simulation, a good mesh is essential to get accurate results, while using a turbulence model and wall function that is correct for the geometry and physics involved. Pressure drop measurements and the corresponding CAD geometries were available at the start of the thesis work. The simulations were adapted to these to nd the sand-grain roughness for the dierent materials. The main conclusions is that the pressure drop can be accurately calculated when the sand-grain roughness is known and the CFD simulation is well dened. It was found from the mesh sensitivity study that it is essential that the rst cell size is at least twice the size of the sand-grain roughness and that at least two cell layers are used to resolve the turbulent boundary layer.
31
Jain, Ruchi V. "Optimization of energy parameters in buildings." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/40445.
Full textAbstract:
Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2007.Includes bibliographical references (p. 34).
When designing buildings, energy analysis is typically done after construction has been completed, but making the design decisions while keeping energy efficiency in mind, is one way to make energy-efficient buildings. The conscious design of building parameters could decrease or completely eliminate the need for Heating, Ventilation and Air Conditioning systems, and thus, optimizing building parameters could help conserve a great amount of energy. This work focuses on two buildings - a passive solar house and an apartment in Beijing. The Beijing apartment is used to study natural ventilation in a space. Both buildings are modeled using EnergyPlus, and analyzed using VBA in Excel. The Genetic Algorithm Optimization Toolbox (GAOT) is used to optimize the parameters for the solar house. The program was run for 150 generations, with there being 20 individuals in each population. The optimized parameters for the solar house resulted in a mean internal temperature of 20.1 C, 7 C lower than that for randomly chosen parameters. The extreme temperatures in both cases were also markedly different, with the optimized parameters providing a more comfortable atmosphere in the house.
(cont.) The apartment parameters were not optimized due to the inherent difficulty in quantifying an objective function. Through the simulation however, it was determined that each window has mass inflow and outflow occurring at the same time. In order to check that mass was conserved through the flow of air in and out of the apartment, the net flow in or out through each window had to be considered. This comparison did show the conservation of mass, which provided confidence in the EnergyPlus model used.
by Ruchi V. Jain.
S.B.
32
Weitzel, T. Timothy. "Optimization of sweet sorghum processing parameters." Thesis, Virginia Polytechnic Institute and State University, 1987. http://hdl.handle.net/10919/80180.
Full textAbstract:
Production of fuel ethanol from renewable biomass sources has gained popularity in recent years. Sweet sorghum is one of the crops identified as an efficient producer of the sugars needed for ethanol production.
The juice in the sweet sorghum pith contains the greatest proportion of nonstructural carbohydrates, the presumed fermentable material. Sugar cane milling procedures have previously been used to extract the juices from the sweet sorghum plant material.
The research reported herein relates to a new method of juice extraction expected to provide higher juice expression efficiencies than previous methods. The sweet sorghum stalks are chopped and the sugar-laden pith fraction is separated from the fibrous rind-leaf. The pith portion only is then fed through a screw press for juice extraction.
Several chopping and separating parameters were evaluated. A statistical linear regression analysis was employed to evaluate the effects of feed rate, cutting interval, chopper knife speed, and percent of whole stalk mass segregated into the pith category on juice yield.
The analysis revealed that the pith category had the most significant positive effect on juice yield calculated as a percent of whole stalk mass. The highest pith categories provided optimization of juice expression. Feed rate has a negative effect on juice yield, meaning that slower feed rates were better, but this was the least significant parameter. The chopping interval had a positive effect, meaning that the largest value used in the analysis provided for optimum juice yield. The cutting speed parameter has no effect on juice yield.Master of Science
33
Titova, Polina. "Optimization of statistical parameters of Eberhard inequality." Thesis, Linnéuniversitetet, Institutionen för matematik (MA), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-39641.
Full textAbstract:
This work is devoted to mathematical modeling of the parameters of the Eberhard inequality using optimization techniques. One of the main purposes of this study is to consider the more general case when the detectors have different efficiencies. In this paper we consider the optimization of parameters for the Eberhard inequality using coefficient of variation taking into account possible errors in the setup of angles during the experiment.
34
Gustavsson, Jonas. "Automated Performance Optimization of GSM/EDGE Network Parameters." Thesis, Linköping University, Linköping University, Communication Systems, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-52565.
Full textAbstract:
The GSM network technology has been developed and improved during several years which have led to an increased complexity. The complexity results in more network parameters and together with different scenarios and situations they form a complex set of configurations. The definition of the network parameters is generally a manual process using static values during test execution. This practice can be costly, difficult and laborious and as the network complexity continues to increase, this problem will continue to grow.This thesis presents an implementation of an automated performance optimization algorithm that utilizes genetic algorithms for optimizing the network parameters. The implementation has been used for proving that the concept of automated optimization is working and most of the work has been carried out in order to use it in practice. The implementation has been applied to the Link Quality Control algorithm and the Improved ACK/NACK feature, which is an apart of GSM EDGE Evolution.
GSM-nätsteknologin har utvecklats och förbättrats under lång tid, vilket har lett till en ökad komplexitet. Denna ökade komplexitet har resulterat i fler nätverksparameterar, tillstånd och standarder. Tillsammans utgör de en komplex uppsättning av olika konfigurationer. Dessa nätverksparameterar har hittills huvudsakligen bestämts med hjälp av en manuell optimeringsprocess. Detta tillvägagångssätt är både dyrt, svårt och tidskrävande och allt eftersom komplexiteten av GSM-näten ökar kommer problemet att bli större.Detta examensarbete presenterar en implementering av en algoritm för automatiserad optimering av prestanda som huvudsakligen använder sig av genetiska algoritmer för att optimera värdet av nätverksparametrarna. Implementeringen har använts för att påvisa att konceptet med en automatiserad optimering fungerar och det mesta av arbetet har utförts för att kunna använda detta i praktiken. Implementeringen har tillämpats på Link Quality Control-algoritmen och Improved ACK/NACK-funktionaliteten, vilket är en del av GSM EDGE Evolution.
35
Fu, Stefan Xueyan. "Finding Optimal Jetting Waveform Parameters with Bayesian Optimization." Thesis, KTH, Optimeringslära och systemteori, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-231374.
Full textAbstract:
Jet printing is a method in surface mount technology (SMT) in which small volumes of solder paste or other electronic materials are applied to printed circuit boards (PCBs). The solder paste is shot onto the boards by a piston powered by a piezoelectric stack. The characteristics of jetted results can be controlled by a number of factors, one of which is the waveform of the piezo actuation voltage signal. While in theory any waveform is possible, in practice, the signal is defined by seven parameters for the specific technology studied here. The optimization problem of finding the optimal parameter combination cannot be solved by standard derivative based methods, as the objective is a black-box function which can only be sampled though noisy and time-consuming evaluations. The current method for optimizing the parameters is an expert guided grid search of the two most important parameters, while the remaining five are kept constant at default values. Bayesian optimization is a heuristic model based search method for efficient optimization of possibly noisy functions with unavailable derivatives. An implementation of the Bayesian optimization algorithm was adapted for the optimization of the waveform parameters, and used to optimize various combinations of the parameters. Results from different trials produced similar values for the two known parameters, with differences within the uncertainty caused by noise. For the remaining five parameters results were more ambiguous. However, a closer examination of the model hyperparameters showed that these five parameters had almost no impact on the objective function. Thus, the best found parameter values were affected more by random noise than the objective. It is concluded that Bayesian optimization might be a suitable and effective method for waveform parameter optimization, and some directions for further development are suggested based on the results of this project.Jet printing är en metod för att applicera lodpasta eller andra elektroniska material på kretskort inom ytmontering inom elektronikproduktion. Lodpastan skjuts ut på kretskorten med hjälp av en pistong som drivs av piezoelektrisk enhet. Kvaliteten på det jettade resultatet kan påverkas av en mängd faktorer, till exempel vågformen av signalen som används för att aktivera piezoenheten. I teorin är vilken vågform som helst möjlig, men i praktiken används en vågform som definieras av sju parametrar. Att hitta optimala värden på dessa parametrar är ett optimeringsproblem som inte kan lösas med metoder baserade på derivata, då optimeringens målfunktion är en s.k. svart låda (black-box function) som bara är tillgänglig via brusiga och tidskrävande evalueringar. Den nuvarande metoden för optimering av parametrarna är en modifierad gridsökning för de två viktigaste parametrarna där de kvarvarande fem parametrarna är fixerade. Bayesiansk optimering är en heuristisk modell-baserad sökmetod för dataeffektiv optimering av brusiga funktioner för vilka derivator inte kan beräknas. En implementation av Bayesiansk optimering anpassades för optimering av vågformsparametrar och användes för att optimera en mängd kombinationer av parametrarna. Alla resultaten gav liknande värden för de två kända parametrarna, med skillnader inom osäkerheten från mätbrus. Resultaten för de övriga fem parametrarna var motstridiga, men en närmare granskning av hyperparametrar för modellen visade att detta berodde på att de fem parametrarna bara har en minimal påverkan på det jettade resultatet. Därför kan de motstridiga resultaten förklaras helt som skillnader på grund av mätbrus. Baserat på resultaten verkar Bayesiansk optimering vara en passande och effektiv metod för optimering av vågformsparametrar. Slutligen föreslås några möjligheter för vidare utveckling av metoden.
36
Van, Eeden Madel. "Determining appropriate parameters for optimization of biocontrol success." Thesis, University of Pretoria, 2013. http://hdl.handle.net/2263/30784.
Full textAbstract:
Increased economic and environmental pressures have led to the requirement
for a more accurate and safe crop protection method. Although Avogreen®
(Bacillus subtilis) offers an environmental friendly alternative to the use of
pesticides; few growers have opted for this approach mainly due to uncertainty
regarding the success of the biocontrol program. Biocontrol success may be
influenced by biological, ecological, scientific, economic, political, social, legal
and marketing factors. Investigations showed that delivery of the antagonist to
the plant surface was equally effective employing a mistblower application
method and a handgun application method. On the leaf, the leaf carrying
capacity influenced survival of the antagonist and the optimal application
concentration of Avogreen®. Increased application frequency and a pre- harvest
spray showed potential to increase biological control efficiency. Foliar fertilizers
and oils enhanced antagonist counts, while spreaders, stickers and copper
containing fungicides inhibited antagonist growth. Social factors that influenced
farmer acceptability towards biological control programs included educational
level, land owner status, generation of farming, land claim status and food safety
system certification. Marketing hurdles facing the South African avocado
industry included frustrations with the registration procedure of new products in
South Africa and a lack of biocontrol knowledge demonstrated by sales staff.
Two disease assessment methods were also evaluated. The conventional
assessment method involving a rating scale was compared to a disease
incidence and severity assessment method. The disease incidence and severity
assessment method allowed a more detailed assessment of disease control
effectiveness. To evaluate the overall success of the biocontrol program a
Biocontrol Assessment Scheme (BAS) was also developed. BAS identified
orchard management, antagonist application practices and technical knowledge
and assistance during marketing as potential restrictions for successful
biocontrol.Thesis (PhD)--University of Pretoria, 2013.
Microbiology and Plant Pathology
Unrestricted
37
Andersson, Axel. "Optimized Tuning of Parameters for HVDC Dynamic Performance Studies." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-193702.
Full textAbstract:
HVDC (High Voltage Direct Current) is used all over the world for transmission of electric power due to lower losses compared to traditional HVAC (High Voltage Alternating Current). However, the procedure of converting AC into DC puts great demand on the control system of the converter stations. These control systems need to be tuned properly to give the HVDC system the correct dynamics to handle variations in the network load and other disturbances. In this thesis, it was investigated if optimization algorithms can be used for tuning of the control parameters. Focus was on three parts of the control system, the Current Control Amplifier, Voltage Dependent Current Order Limiter and the Rectifier Alpha Minimum Limiter. The Nelder & Mead Simplex method was used and several different objective functions were tested, including combinations of integral square error, integral absolute error, rise time and overshoot. Several different fault cases and scenarios were tested and results of the optimization were compared to the manually tuned control system. It was found that the results of the optimization were comparable with the manually tuned parameters for many of the cases tested. The biggest issue encountered was that the optimization algorithm often finds a local minimum in the objective function, leading to a suboptimal solution. This issue could be solved by running the optimization several times, using different initial values. It is concluded that using optimization algorithms could be a useful tool for tuning of the HVDC control system.
38
Eren, Tuna. "Real-time-optimization Of Drilling Parameters During Drilling Operations." Phd thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12611558/index.pdf.
Full textAbstract:
Real-time optimization of drilling parameters during drilling operations aims to optimize weight on bit, bit rotation speed for obtaining maximum drilling rate as well as minimizing the drilling cost. The process is considered to be formation specific. A statistical method such as multiple linear regression technique has been used for the drilling optimization. An extensive literature survey on drilling optimization was conducted for this research study. A model is developed for this purpose using actual field data collected through modern well monitoring and data recording systems, which predicts the rate of drilling penetration as a function of available parameters. The rate of penetration general equation is optimized for effective functions at each data point. In order to optimize the parameters in the field, a computer network is required to be developed. The computer network will keep the piped data directly from the data source, and continuously be collecting the new data to be fed. A database present at the central computer will be continuously calculating the developed model parameters by means of multiple regression technique and inform the team at the field. The field engineer will transmit the current drilling parameters back to the central computer, and the headquarters will determine the new model parameters and optimum drilling parameters by including the recently received information. Therefore, there will be a real-time-optimization process. It is considered that this technique is going to be widely used in future drilling activities since it could reduce drilling costs and minimize probability of encountering problems due to working with optimized parameters.
It has been found that drilling rate of penetration could be modelled in real-time environment as a function of independent drilling variables such as weight on bit, rotation speed of the string, drilling fluid weight, and formation characteristics. The ability to have the drilling rate of penetration with respect to depth characteristically with certain parameters for specific formations on real-time basis could bring new insights to the nature of drilling optimization studies. Any significant departure of the actual rate of penetration from the predicted rate of penetration trend could have important indications which could be detected beforehand in real-time. The study has also achieved one of its objectives, giving the optimized independent drilling parameters found following statistical synthesis.
39
Monder, Dayadeep S. "Real-Time Optimization of gasoline blending with uncertain parameters." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ60472.pdf.
Full text
40
Powell, B. Michael. "Surface finish optimization by modification of milling cutter parameters." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/MQ62268.pdf.
Full text
41
Nyström, Birgitha. "Natural fiber composites : optimization of microstructure and processing parameters /." Luleå : Luleå tekniska universitet/Tillämpad fysik, maskin- och materialteknik/Polymerteknik, 2007. http://epubl.ltu.se/1402-1757/2007/31/.
Full text
42
Tulloss, Jr Robert Stuart. "Optimization of Geometric Parameters for a Deployable Space Structure." Thesis, Virginia Tech, 2021. http://hdl.handle.net/10919/104873.
Full textAbstract:
Deployable structures are used for many different spacecraft applications like solar arrays, antennas, and booms. They allow spacecraft with large structural components to comply with the volume restrictions of launch platforms. This research optimizes the shape and size of these structural components with both the stowed and deployed configurations in mind. HEEDS, a commercial optimization software, and ABAQUS, a commercial finite element analysis software, are used to evaluate and alter the structure using a single simulation. This makes the design process more efficient than running many different simulations individually. The optimization objectives, design variables, and constraints are chosen to fit the mission requirements of the structure. The structure analyzed in this research is a composite tube with a compressible cross-section wrapped around a cylinder. The change in cross-section reduces the bending stiffness of the tube and allows it to be wrapped without damaging the material. The dimensions controlling cross-section shape and the thickness of the composite layers are the design variables for the optimization. The maximum strain energy stored in the wrapped tube, the minimum volume of the structure, and the minimum weight of the tube are the objectives for the optimization. The strain energy is maximized to get the stiffest possible structure and satisfy the minimum natural frequency constraint. The weight and volume of the tube are minimized because reducing weight and volume is important for any spacecraft structure. Constraints are placed on the design variables and objectives and the Hashin damage criteria are used to ensure wrapping does not cause material failure. Three optimization runs from different initial designs are completed using SHERPA and genetic algorithm optimization methods. The results are compared to determine which optimization method performs best and how the different starting points affect the final results. After the optimized design is found, the full wrapping and deployment simulation is completed to analyze the behavior of the optimized design.Master of Science
Spacecraft are launched into space using launch vehicles. There is limited room inside the launch vehicle for the spacecraft, but the spacecraft often needs large components like solar panels, antennas, and booms to complete the mission. These components must be designed in a way that allows them to be stowed in a smaller space. This can be accomplished by designing a system that can change the configuration of the component once the spacecraft is in orbit. This is referred to as a deployable structure, and the objective of this research is to create an optimization method for designing this type of structure. This is challenging because both the stowed and deployed configurations must be considered during the optimization. HEEDS, a commercial optimization software, and ABAQUS, a commercial structural analysis software, are used to evaluate and optimize the structure in a single simulation. The optimization objectives, design variables, and constraints are chosen to fit the mission requirements of the structure. The structure examined in this research is a composite tube with a compressible cross-section wrapped around a cylinder. As the tube is wrapped, it flattens, reducing the bending stiffness so the tube can be wrapped without damaging the material. The variables controlling cross-section shape and the thickness of the composite material layers will be altered during the optimization. The maximum strain energy stored in the wrapped tube, the volume of the tube, and the minimum weight of the tube are the objectives for the optimization. The strain energy is maximized to get the stiffest possible tube when it is unwrapped to ensure there is enough stored energy to facilitate the full deployment and to satisfy the minimum natural frequency constraint. The weight and volume of the tube are minimized because reducing weight and volume is important for any spacecraft structure. Constraints are placed on the design variables and objectives and the Hashin damage criteria are used to ensure wrapping does not cause material failure. The Hashin damage criteria use the strength of the material and the stresses on the material to determine if it is likely to fail. Three optimization runs with different starting points are completed for both the SHERPA and genetic algorithm optimization methods. The results are compared to determine which optimization method performs best and how the different starting points affect the final results. After the optimized design is found, the full wrapping and deployment simulation is completed to analyze the behavior of the optimized design.
43
Boggess, Chadwick D. "Optimization of Growth Parameters for Algal Regrowth Potential Experiments." DigitalCommons@CalPoly, 2014. https://digitalcommons.calpoly.edu/theses/1234.
Full textAbstract:
Water cost is one of the key deterrents in making algal biofuels a feasible alternative to traditional petroleum fuels. Research into recycling of algal media was conducted in a laboratory setting at the California Polytechnic State University in San Luis Obispo. A growth assay was created to allow for algal cultures, specifically Ward’s Chlorella sp., to proliferate in sealed culture vessels. Bold’s Basal Medium (BBM) was selected as the media due to its extensive use with freshwater algal strains. However, this medium can limit algal growth through nutrient limitation and it became necessary to augment the original recipe. 50mM of sodium bicarbonate was added to the media in order to buffer the purging of 100% CO2 into the culture vessel. The resultant pH of the CO2 saturated media was 6.25. The elemental? composition of Chlorella vulgaris was compared with the nutrient content of BBM to estimate possible nutrient limitations which could occur throughout growth (Oh Hama, 1988). From this analysis, the nitrogen and phosphorus concentration in BBM was augmented by a factor of three (BBM3N3P). Further, vitamins, specifically cyanocobalamin, thiamine HCL, and biotin, were incorporated after conducting a comparison growth study with BBM 3N3P. The average maximum specific growth rates for the normal BBM and for the vitamin-enhanced BBM were 0.689 +/- 0.0818 and 0.887 +/- 0.1901 (mean +/- std. deviation) per day, respectively. This difference was proved significant by a t-test with a p-value equal to 0.041. A standardized methodology for conducting a regrowth potential experiment was outlined by the research. One phase of this methodology included reintroduction of nutrients consumed during the first round of growth. Prior to continuing with this methodology the effect of supplementing trace metals and micronutrients into the culture was investigated. At a p-value of 0.0956, there was no significant difference between BBM 3N3P + vitamins and the same media with eight times the trace metal and micronutrient concentration. This allowed for up to seven rounds of regrowth with no inhibition caused from the restoration of these nutrients. A final regrowth was conducted on BBM 3N3P + vitamins + 50 mM bicarbonate. A significant difference existed between both the Round 1 and Round 2 cultures, as well as between the Round 2 cultures and their respective controls. This signified the possible release of allelochemicals by the Chlorella sp.. A preliminary investigation into the possible use of anaerobic digester effluent as a primary source of nutrients for algal cultures was also conducted. The digestate (diluted 50% v/v with a saline make-up) grew significantly faster than the controls (p-value<0.001). Further, after the introduction of trace metals and micronutrients the digestate columns outlived the control columns increasing the feasibility of using digestate to supplemental algal cultures.
44
Golovidov, Oleg. "Variable-Complexity Approximations for Aerodynamic Parameters in Hsct Optimization." Thesis, Virginia Tech, 1997. http://hdl.handle.net/10919/36789.
Full textAbstract:
A procedure for generating and using polynomial approximations to the range or to the cruise drag components in terms of 29 design variables for the High Speed Civil Transport (HSCT) configuration and performance design is presented.
Response surface model methodology is used to fit quadratic polynomials to data gathered from a series of numerical analyses of different HSCT designs. Several techniques are employed to minimize the number of required analyses and to maintain accuracy. Approximate analysis techniques
are used to find regions of the design space where reasonable HSCT designs could occur and response surface models are built using higher fidelity analysis results of the designs in this "reasonable" region. Regression analysis and analysis of variance are then used to reduce the number of polynomial terms in the response surface model functions.
Optimizations of the HSCT are then carried out both with and without the response surface models, and the effect of the use of the response surface models is discussed. Results of the work showed that considerable reduction of the amount of numerical noise in optimization is achieved with response surface models and the convergence rate was slightly improved. Careful attention was required to keep the accuracy of the models at an acceptable level.
NOTE: (07/2012) An updated copy of this ETD was added after there were patron reports of problems with the file.Master of Science
45
Chen, Chien-Chan, and 陳建成. "The Parameters Optimization for Milling Operations via Computer Experiment." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/qejm24.
Full textAbstract:
碩士逢甲大學
工業工程學所
91
It is known that cutting time and tool life affects the cost and quality of a manufactured product. Most of the literatures on cutting time or tool life problems have focused on developing exact methods to minimize the manufacturing cost, or maximize the quality value. The inherent assumptions under these approaches are that the cutting time and the tool life equations are known before a problem being analyzed. However, most of time these equations are unknown during the early stage of process planning. In addition, previous works mainly consider the cutting time and tool life aspects as a separate issue for problem formulation. That usually can not ensure the found cutting parameter values are the truly optimal values. With the recent development in CAM (Computer-Aided Manufacturing) software, manufacturing engineers can proceed with the process planning problems, without knowing functional relationship between process input and process output in advance. In this study, the simulation is employed using CATIA V5R8 software to obtain the simulated outputs. The simulated outputs are analyzed by Response Surface Methodology (RSM) to have cutting time and tool life equations. Then, these two equations are placed in one cost function simultaneously which should be minimized in presented problem. Finally, with this function as an objective in problem formulation, the optimal cutting parameter values of milling operations can be found by optimization technique such as mathematical programming easily.
46
Wang, Yi-Chi, and 王逸琦. "The Ergonomic Parameters Optimization for Product Design via Computer Musculoskeletal Modeling." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/80492275225005472187.
Full textAbstract:
碩士逢甲大學
工業工程與系統管理學系
104
This research is to determine the optimum parameter values for an ergonomic product designs via computer musculoskeletal modeling and multi-objective optimization. The muscle activities measured from AnyBody (AB) Modeling System for multiple muscle applications are used to develop the functional relationships and build ANOVA via the statistical method, such as Response Surface Methodology (RSM). These functional relationships are considered as objective functions which will be further formulated as a compromise multi-objective optimization problem. A bike-frame design problem in designing the length of stem, head tube, fork, top tube, seat post, seat tube, and pedal crank is chosen as an example to demonstrate the proposed method. Because the combination of computer musculoskeletal modeling, statistical method, and optimization technique are realized in proposed approach, the ergonomic product designs for safety and health can be achieved in the stage of product design.
47
Yu, Hsiu-Ling, and 游繡綾. "Parameter optimization for heat conduction structure in industrial computer." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/9mur28.
Full textAbstract:
碩士國立臺北科技大學
製造科技研究所
106
In dedicated embedded computers, the operating temperature range from low to very high temperatures to fulfil special requirements. This trend makes an electronic device generate more heat. Heat dissipation appears to be a vital factor. This research applies a multi-heat pipe structure concept to design the thermal module in a limited space. The design makes the cooling medium have more freedom on mobility, and improves the heat pipe thermal dissipation. The Taguchi method was used to investigate the optimal design parameters of heat conduction structure. The four control factors selected are heat dissipation module main structure, CPU heat conduction material, wedge lock heat conduction material, and the back cover material. The quality objective considered is the thermal resistance of the wedge lock calculated from the experimental data. Take the Smaller the Better (STB) to be the quality evaluation method. In this case study, experimental results show the best parameter combination is heat dissipation module main structure is Aluminium with pipe no soldering、CPU heat conduction material is thermal grease、wedge lock doesn’t need the heat conduction material and back cover material is galvanized steel. . In comparison with the existing heat dissipation module, the CPU-to-environment total thermal resistance from 2.215°C/W down to 1.49°C/W. Reduction rate is around 67%.
48
Liao, Yu-Pei, and 廖渝珮. "Robust parameter and tolerance design for maximized NB CPU life via computer experiment and statistical optimization." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/62300934769723670950.
Full text
49
"Parameter optimization and learning for 3D object reconstruction from line drawings." 2010. http://library.cuhk.edu.hk/record=b5894303.
Full textAbstract:
Du, Hao.Thesis (M.Phil.)--Chinese University of Hong Kong, 2010.
Includes bibliographical references (p. 61).
Abstracts in English and Chinese.
Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- 3D Reconstruction from 2D Line Drawings and its Applications --- p.1
Chapter 1.2 --- Algorithmic Development of 3D Reconstruction from 2D Line Drawings --- p.3
Chapter 1.2.1 --- Line Labeling and Realization Problem --- p.4
Chapter 1.2.2 --- 3D Reconstruction from Multiple Line Drawings --- p.5
Chapter 1.2.3 --- 3D Reconstruction from a Single Line Drawing --- p.6
Chapter 1.3 --- Research Problems and Our Contributions --- p.12
Chapter 2 --- Adaptive Parameter Setting --- p.15
Chapter 2.1 --- Regularities in Optimization-Based 3D Reconstruction --- p.15
Chapter 2.1.1 --- Face Planarity --- p.18
Chapter 2.1.2 --- Line Parallelism --- p.19
Chapter 2.1.3 --- Line Verticality --- p.19
Chapter 2.1.4 --- Isometry --- p.19
Chapter 2.1.5 --- Corner Orthogonality --- p.20
Chapter 2.1.6 --- Skewed Facial Orthogonality --- p.21
Chapter 2.1.7 --- Skewed Facial Symmetry --- p.22
Chapter 2.1.8 --- Line Orthogonality --- p.24
Chapter 2.1.9 --- Minimum Standard Deviation of Angles --- p.24
Chapter 2.1.10 --- Face Perpendicularity --- p.24
Chapter 2.1.11 --- Line Collinearity --- p.25
Chapter 2.1.12 --- Whole Symmetry --- p.25
Chapter 2.2 --- Adaptive Parameter Setting in the Objective Function --- p.26
Chapter 2.2.1 --- Hill-Climbing Optimization Technique --- p.28
Chapter 2.2.2 --- Adaptive Weight Setting and its Explanations --- p.29
Chapter 3 --- Parameter Learning --- p.33
Chapter 3.1 --- Construction of A Large 3D Object Database --- p.33
Chapter 3.2 --- Training Dataset Generation --- p.34
Chapter 3.3 --- Parameter Learning Framework --- p.37
Chapter 3.3.1 --- Evolutionary Algorithms --- p.38
Chapter 3.3.2 --- Reconstruction Error Calculation --- p.39
Chapter 3.3.3 --- Parameter Learning Algorithm --- p.41
Chapter 4 --- Experimental Results --- p.45
Chapter 4.1 --- Adaptive Parameter Setting --- p.45
Chapter 4.1.1 --- Use Manually-Set Weights --- p.45
Chapter 4.1.2 --- Learn the Best Weights with Different Strategies --- p.48
Chapter 4.2 --- Evolutionary-Algorithm-Based Parameter Learning --- p.49
Chapter 5 --- Conclusions and Future Work --- p.53
Bibliography --- p.55
50
Lundgren, Martin. "Optimizing a Water Simulation based on Wavefront Parameter Optimization." Thesis, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-14788.
Full textAbstract:
DICE, a Swedish game company, wanted a more realistic water simulation. Currently, most large scale water simulations used in games are based upon ocean simulation technology. These techniques falter when used in other scenarios, such as coastlines. In order to produce a more realistic simulation, a new one was created based upon the water simulation technique "Wavefront Parameter Interpolation". This technique involves a rather extensive preprocess that enables ocean simulations to have interactions with the terrain. This paper is about optimizing the current implementation of DICE's water simulation. The goal is to achieve better runtime GPU performance. After implementing various optimizations, a speedup of roughly 4-6x was achieved. Performance was evaluated on the PlayStation 4 gaming console.DICE, ett svenskt spelföretag, ville ha en mer realistisk vattensimulering. Det flesta storskalna vattensimuleringar som används i spel idag är baserade på havsvattensimuleringstekniker. Dessa tekniker fungerar inte lika bra i andra scenarier, som t.ex. kustlinjer. För att kunna få en mer realistisk simulation, skapades en ny simulation baserad på vattensimuleringstekniken Wavefront Parameter Interpolation. Denna simuleringsteknik involverar en lång förprocess som ger havsvattensimuleringar möjligheten att interagera med terräng. Denna uppsats handlar om att optimera den nuvarande implementationen av DICEs vattensimulering. Målet är att få bättre grafikprestanda under körtid. Efter att olika optimiseringar hade implementerats, blev programmet 4-6x gånger snabbare. Prestandan utvärderades på spelkonsolen PlayStation 4.