Relevant bibliographies by topics / Optimization parameters

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Optimization parameters'

Author: Grafiati
Published: 28 May 2022
Last updated: 18 July 2025

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Journal articles on the topic "Optimization parameters"

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Zhang, Qiantu, Liqing Fang, Leilei Ma, and Yulong Zhao. "Research on Parameters Optimization of SVM Based on Improved Fruit Fly Optimization Algorithm." International Journal of Computer Theory and Engineering 8, no. 6 (2016): 500–505. http://dx.doi.org/10.7763/ijcte.2016.v8.1096.

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Khare, Manu, and Deepak Kumar Deepak Kumar. "Optimization of Sand Casting Parameters using Factorial Design." International Journal of Scientific Research 3, no. 1 (2012): 151–53. http://dx.doi.org/10.15373/22778179/jan2014/49.

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Marko, Hrelja, Klancnik Simon, Irgolic Tomaz, Paulic Matej, Balic Joze, and Brezocnik Miran. "Turning Parameters Optimization Using Particle Swarm Optimization." Procedia Engineering 69 (2014): 670–77. http://dx.doi.org/10.1016/j.proeng.2014.03.041.

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Дьяков, Иван, and Ivan D'yakov. "OPTIMIZATION OF TIRE PARAMETERS." Bulletin of Bryansk state technical university 2018, no. 9 (2018): 33–38. http://dx.doi.org/10.30987/article_5bd17b4722c1f0.54739329.

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Aly, Nael A. "Optimization of testability parameters." Computers & Industrial Engineering 17, no. 1-4 (1989): 333–39. http://dx.doi.org/10.1016/0360-8352(89)90084-3.

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Rajeanderan Revichandran, Jaffar Syed Mohamed Ali, Moumen Idres, and A. K. M. Mohiuddin. "A Review of HVAC System Optimization and Its Effects on Saving Total Energy Utilization of a Building." Journal of Advanced Research in Fluid Mechanics and Thermal Sciences 93, no. 1 (2022): 64–82. http://dx.doi.org/10.37934/arfmts.93.1.6482.

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The paper illustrates the review on the optimizations studies of HVAC systems based on three main methods – HVAC operational variables optimization, optimization of control parameters in HVAC system and parameter optimization in building models. For the HVAC system’s operational variables, the optimization process is based on the common and prescient energy utilization models. Thus, by comparing both, the non-common HVAC system models can get better output of energy reduction. Based on most of the studies, the occupancies thermal comfort requirements, are represented by the indoor air quality (IAQ) or the predicted mean vote (PMV) indexes. Comparing both requirements, the PMV index had a better overall energy reduction output of 47% and estimated annual energy reduction of 2,769 kg/year. Meanwhile, in optimization of HVAC’s control parameters, its overall aim is to achieve a better response output of the HVAC system in order to prevent energy wastage. Among this different optimization’s controller, the fuzzy logic tuning optimization has a better overall energy reduction. On the other hand, the parameter optimization in building model approach is performed before the construction of the structure itself, where multiple construction parameters are considerations in the design. In overall, when different tools for building parameter and model optimization are compared, the EXRETopt by using PMV comfort index approximately reduces 62% of the energy utilization.
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Abd El-Hamid, Ahmed S., Ahmed H. Eissa, and ALy M. Radwan. "Levenberg – Marquardt’s Algorithm used for PID Controller Parameters Optimization." International Journal of Engineering Research 4, no. 6 (2015): 286–90. http://dx.doi.org/10.17950/ijer/v4s6/603.

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S, Rajesh A., and Dr M. S. Prabuswamy. "An Overview of PSO in Optimization of Machining Parameters." International Journal of Trend in Scientific Research and Development Volume-2, Issue-2 (2018): 150–57. http://dx.doi.org/10.31142/ijtsrd8383.

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Minglin, Chen, Lv Enli, and Gan Ling. "Experimental Optimization Of Litchi Spray Pre-Cooling Process Parameters." American Journal of Engineering And Techonology 02, no. 08 (2020): 45–52. http://dx.doi.org/10.37547/tajet/volume02issue08-06.

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Kumar, Ramesh, Ashwani Kumar, Laxmikant Laxmikant, Nitesh Dutt, and Varun Pratap Singh. "Cutting Parameters Optimization in Turning Operation using Taguschi Method." International Journal of Materials Manufacturing and Sustainable Technologies 1, no. 2 (2022): 22–30. http://dx.doi.org/10.56896/ijmmst.2022.1.2.009.

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The objective of this study is to optimise the cutting parameters in Turning Operation. For this objective Taguchi Method was used. S/N ratio, ANNOVA was used to investigate the cutting force components & Material removal rate (MRR). In results optimal cutting parameters were obtained and the factors affecting cutting performance were analysed. It was concluded that cutting parameters i.e. depth of cut has influence on cutting force and material removal rate.
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Dissertations / Theses on the topic "Optimization parameters"

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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.

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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.
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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.

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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.
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Johansson, Christopher. "Optimization of wall parameters using CFD." Thesis, KTH, Aerodynamik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-159875.

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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.
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Jain, Ruchi V. "Optimization of energy parameters in buildings." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/40445.

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Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2007.<br>Includes bibliographical references (p. 34).<br>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.<br>(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.<br>by Ruchi V. Jain.<br>S.B.
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Weitzel, T. Timothy. "Optimization of sweet sorghum processing parameters." Thesis, Virginia Polytechnic Institute and State University, 1987. http://hdl.handle.net/10919/80180.

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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.<br>Master of Science
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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.

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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.
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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.

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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 &amp; 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.
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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.

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<p>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.</p><br><p>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.</p>
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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.

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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.<br>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.
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Van, Eeden Madel. "Determining appropriate parameters for optimization of biocontrol success." Thesis, University of Pretoria, 2013. http://hdl.handle.net/2263/30784.

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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.<br>Thesis (PhD)--University of Pretoria, 2013.<br>Microbiology and Plant Pathology<br>Unrestricted
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Books on the topic "Optimization parameters"

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M, Adelman Howard, Sobieski Jaroslaw, and Langley Research Center, eds. Optimization for minimum sensitivity to uncertain parameters. National Aeronautics and Space Administration, Langley Research Center, 1994.

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M, Plencner Robert, Seidel Jonathan A, and United States. National Aeronautics and Space Administration., eds. Concurrent optimization of airframe and engine design parameters. National Aeronautics and Space Administration, 1992.

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Moayyedian, Mehdi. Intelligent Optimization of Mold Design and Process Parameters in Injection Molding. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-03356-9.

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United States. National Aeronautics and Space Administration., ed. User's manual for an aerodynamic optimization scheme that updates flow variables and design parameters simultaneously. Flow Research, Inc., Applied Mechanics Division, 1989.

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S, Salzar Robert, and United States. National Aeronautics and Space Administration., eds. Optimization of residual stresses in MMC's through the variation of interfacial layer architectures and processing parameters. National Aeronautics and Space Administration, 1996.

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S, Salzar Robert, and United States. National Aeronautics and Space Administration., eds. Optimization of residual stresses in MMC's through the variation of interfacial layer architectures and processing parameters. National Aeronautics and Space Administration, 1996.

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Lerch, F. J. Optimum data weighting and error calibration for estimation of gravitational parameters. National Aeronautics and Space Administration, Goddard Space Flight Center, 1989.

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IUTAM Symposium on Field Analyses for Determination of Material Parameters-- Experimental and Numerical Aspects (2000 Kiruna, Sweden). IUTAM Symposium on Field Analyses for Determination of Material Parameters-- Experimental and Numerical Aspects. Kluwer Academic Publishers, 2003.

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Mischenko, Aleksandr, and Anastasiya Ivanova. Optimization models for managing limited resources in logistics. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1082948.

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In the proposed monograph, optimization models for managing limited resources in logical systems are considered. Such systems are primarily used by industrial enterprises, transport companies and trade organizations, including those that carry out wholesale activities. As a rule, the efficiency of these objects largely depends on how rational use of limited resources such as: consumer camera business, labor, vehicles, etc. In this paper, various approaches to managing such resources are considered both for deterministic models and for the situation when a number of model parameters are not specified exactly, that is, for stochastic models. In this case, it is proposed to evaluate the stability of models to the occurrence of various types of risk events, both by the structure of the solution and by the functionality. It is addressed to senior students, postgraduates and masters studying in the specialty "Management" and "Logistics", as well as specialists in the field of logistics systems modeling.
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Bowers, Charles Emery. An assessment of competing facility location optimization parameters: A case study of the United States Navy, Morale Welfare and Recreation Facilities. Available from National Technical Information Service, 2000.

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Book chapters on the topic "Optimization parameters"

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Zlobec, Sanjo. "Locally Optimal Parameters." In Applied Optimization. Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-0011-7_8.

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Zlobec, Sanjo. "Globally Optimal Parameters." In Applied Optimization. Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-0011-7_9.

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Guan, Zhichuan, Tinggen Chen, and Hualin Liao. "Drilling Parameters Optimization." In Theory and Technology of Drilling Engineering. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-9327-7_4.

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Mann, Felix, and Bernard Ries. "Blocking Graph Parameters." In Encyclopedia of Optimization. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-030-54621-2_902-1.

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Gil-Aluja, Jaime. "Estimating economic parameters in investment." In Applied Optimization. Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-5328-7_11.

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Dombrovskaya, Henrietta, Boris Novikov, and Anna Bailliekova. "What About Configuration Parameters?" In PostgreSQL Query Optimization. Apress, 2024. http://dx.doi.org/10.1007/979-8-8688-0069-6_10.

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Kakandikar, Ganesh M., and Vilas M. Nandedkar. "Process Parameters in Drawing." In Sheet Metal Forming Optimization. CRC Press, 2017. http://dx.doi.org/10.4324/9781315156101-2.

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Constantinescu, Tiberiu. "Determinantal Formulae and Optimization." In Schur Parameters, Factorization and Dilation Problems. Birkhäuser Basel, 1996. http://dx.doi.org/10.1007/978-3-0348-9108-0_8.

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Sciacca, Eva, and Salvatore Spinella. "Reliable Biological Circuit Design Including Uncertain Kinetic Parameters." In Fuzzy Optimization. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13935-2_21.

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Pardalos, Panos M., Pavel S. Knopov, Stanislav P. Uryasev, and Vitaliy A. Yatsenko. "Optimal Estimation of Signal Parameters Using Bilinear Observations." In Applied Optimization. Springer US, 2001. http://dx.doi.org/10.1007/978-1-4757-6099-6_8.

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Conference papers on the topic "Optimization parameters"

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Vanghi, V., and C. Chevallier. "WCDMA handover parameters optimization." In 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577). IEEE, 2004. http://dx.doi.org/10.1109/icc.2004.1313326.

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Tekin, Yasar. "Optimization of LDA parameters." In 2020 28th Signal Processing and Communications Applications Conference (SIU). IEEE, 2020. http://dx.doi.org/10.1109/siu49456.2020.9302034.

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Loderer, Marek, and Jarmila Pavlovicova. "Optimization of LBP parameters." In 2014 56th International Symposium ELMAR. IEEE, 2014. http://dx.doi.org/10.1109/elmar.2014.6923329.

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Kryuchkov, A. V., and A. I. Grishin. "Optimization parameters of ceilometer." In XXI International Symposium Atmospheric and Ocean Optics. Atmospheric Physics, edited by Oleg A. Romanovskii. SPIE, 2015. http://dx.doi.org/10.1117/12.2205996.

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Alsayyed, Basel, and Frederick O. Malm. "Waterjet Process Parameters Optimization." In ASME 2023 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/imece2023-115307.

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Abstract Abrasive Water Jet Machining (AWJM) is a non-conventional machining process widely used in modern manufacturing industries due to its versatile cutting capabilities. The optimal performance of AWJM depends on the appropriate selection of process input parameters, which include water pressure, abrasive mass flow rate, material thickness, and cutting feed. However, the impact of material thickness variation on the AWJM process has been overlooked in previous research studies. To address this research gap, this study aims to investigate the effect of material thickness variation on the performance of AWJM and incorporate it as a factor in the process input parameters. The study methodology will employ the Taguchi orthogonal array and Analysis of Variance (ANOVA) to determine the optimal levels of process parameters for aluminum 6061 T65. The Design of Experiment (DoE) model will be set up based on the four input factors and their levels. Experiments will be conducted using the A-0612 WARDJet machine to achieve the best quality characteristics regarding the material removal rate (MMR) and the surface roughness Ra for different materials. By considering material thickness as a factor in the analysis of responses, this study seeks to enhance the understanding of the interrelationship between process input parameters and material thickness variation in AWJM. The study findings are expected to provide valuable insights to improve process efficiency and effectiveness, leading to better-quality outcomes in modern manufacturing industries.
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Bashashati, Hossein, Rabab K. Ward, and Ali Bashashati. "Bayesian optimization of BCI parameters." In 2016 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE). IEEE, 2016. http://dx.doi.org/10.1109/ccece.2016.7726801.

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Libao An and Mingyuan Chen. "On Optimization of Machining Parameters." In 4th International Conference on Control and Automation. Final Program and Book of Abstracts. IEEE, 2003. http://dx.doi.org/10.1109/icca.2003.1595141.

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Bengio, Y. "Continuous optimization of hyper-parameters." In Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium. IEEE, 2000. http://dx.doi.org/10.1109/ijcnn.2000.857853.

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Seabra, A., Theodore E. Simos, George Psihoyios, and Ch Tsitouras. "Optimization of Mechanical Systems Parameters." In ICNAAM 2010: International Conference of Numerical Analysis and Applied Mathematics 2010. AIP, 2010. http://dx.doi.org/10.1063/1.3498508.

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Tawdross, Peter, and Andreas Konig. "Local Parameters Particle Swarm Optimization." In 2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06). IEEE, 2006. http://dx.doi.org/10.1109/his.2006.264935.

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Reports on the topic "Optimization parameters"

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Emanuel, Kerry A. Variational Optimization of Sub-Grid Scale Convection Parameters. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/760094.

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Thompson, Kathleen A. Optimization of NLC machine parameters for specific physics processes. Office of Scientific and Technical Information (OSTI), 1999. http://dx.doi.org/10.2172/15065.

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Sittaramane, Azhagapattar, and Govindarajan Mahendran. Optimization of Diffusion Bonding Parameters of Dissimilar Aluminium Matrix Composites. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, 2019. http://dx.doi.org/10.7546/crabs.2019.04.11.

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Zivkovic-Rothman, M. Variational optimization of sub-grid scale convection parameters. Final report. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/663533.

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Green, D. Optimization of CMS HCAL parameters using hanging file test data. Office of Scientific and Technical Information (OSTI), 1994. http://dx.doi.org/10.2172/10169953.

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Ng, Melissa R., Bryan Moran, Logan Bekker, and Nikola Dudukovic. Large Area Projection Microstereolithography: Characterization and Optimization of 3D Printing Parameters. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1305839.

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Hamrick, Todd. Optimization of Operating Parameters for Minimum Mechanical Specific Energy in Drilling. Office of Scientific and Technical Information (OSTI), 2011. http://dx.doi.org/10.2172/1060223.

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Ovalle, Samuel, E. Viamontes, and Tony Thomas. Optimization of DLP 3D Printed Ceramic Parts. Florida International University, 2021. http://dx.doi.org/10.25148/mmeurs.009776.

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Digital Light Processing (DLP) 3D printing allows for the creation of parts with advanced engineering materials and geometries difficult to produce through conventional manufacturing techniques. Photosensitive resin monomers are activated with a UV-producing LCD screen to polymerize, layer by layer, forming the desired part. With the right mixture of photosensitive resin and advanced engineering powder material, useful engineering-grade parts can be produced. The Bison 1000 is a research-grade DLP printer that permits the user to change many parameters, in order to discover an optimal method for producing 3D parts of any material of interest. In this presentation, the process parameter optimization and their influence on the 3D printed parts through DLP technique will be discussed. The presentation is focused on developing 3D printable slurry, printing of complex ceramic lattice structures, as well as post heat treatment of these DLP-produced parts.
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Desjardins. L52204 Framework for the Optimization of Inspection Intervals. Pipeline Research Council International, Inc. (PRCI), 2004. http://dx.doi.org/10.55274/r0011352.

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The goal of this project is to develop a methodology to find the optimal inspection timing of pipelines carrying hazardous materials. The four principle parameters affecting the need for inspection are: - Anomaly severity - Deterioration rate Limit state - Consequences of failure In addition to these parameters, considered in this research, uncertainty needs to be understood and accounted for. Knowledge of each of the above parameters is limited by various factors. Morrison has chosen to approach this uncertainty with a probabilistic method that leads to a risk and reliability solution. As applicable to the optimization of inspection timing, the goal of this report is to provide a set of procedures to: - Assess pipeline integrity - Assess corrosion rates Predict future corrosion severity - Predict the increase of probability of failure (POF), reliability, and risk as a function of time and location along the pipeline - Optimize inspection, repair, and mitigation programs to maintain target integrity levels There is software related to this research.
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Fink, Bruce K., Roopesh Mathur, and Suresh G. Advani. On the Application of Genetic Algorithms for Optimization of RTM Process Parameters. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada383812.

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