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Dissertations / Theses on the topic 'Particle swarm optimization techniques'

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Published: 5 June 2025

Last updated: 2 August 2025

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1

Wilke, Daniel N. "Analysis of the particle swarm optimization algorithm." Pretoria : [s.n.], 2005. http://upetd.up.ac.za/thesis/available/etd-01312006-125743.

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2

Franz, Wayne. "Multi-population PSO-GA hybrid techniques: integration, topologies, and parallel composition." Springer, 2013. http://hdl.handle.net/1993/23842.

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Recent work in metaheuristic algorithms has shown that solution quality may be improved by composing algorithms with orthogonal characteristics. In this thesis, I study multi-population particle swarm optimization (MPSO) and genetic algorithm (GA) hybrid strategies. I begin by investigating the behaviour of MPSO with crossover, mutation, swapping, and all three, and show that the latter is able to solve the most difficult benchmark functions. Because GAs converge slowly and MPSO provides a large degree of parallelism, I also develop several parallel hybrid algorithms. A composite approach exec

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Sheehan, Shane P. "Spacecraft Trajectory Optimization Suite (STOPS): Optimization of Low-Thrust Interplanetary Spacecraft Trajectories Using Modern Optimization Techniques." DigitalCommons@CalPoly, 2017. https://digitalcommons.calpoly.edu/theses/1901.

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The work presented here is a continuation of Spacecraft Trajectory Optimization Suite (STOpS), a master’s thesis written by Timothy Fitzgerald at California Polytechnic State University, San Luis Obispo. Low-thrust spacecraft engines are becoming much more common due to their high efficiency, especially for interplanetary trajectories. The version of STOpS presented here optimizes low-thrust trajectories using the Island Model Paradigm with three stochastic evolutionary algorithms: the genetic algorithm, differential evolution, and particle swarm optimization. While the algorithms used here we

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4

Ural, Mustafa. "Solution Of The Antenna Placement Problem By Means Of Global Optimization Techniques." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612674/index.pdf.

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In this thesis work, minimization of platform-based coupling between the antennas of two VHF radios on an aircraft platform and two HF radios on a ship platform is aimed. For this purpose<br>an optimal antenna placement, which yields minimum average coupling between the antennas over the whole frequency band of operation is determined for each platform. Two important global optimization techniques, namely Genetic Algorithm Optimization and Particle Swarm Optimization, are used in determination of these optimal antenna placements. Aircraft &amp<br>ship platforms and antennas placed on them are

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5

Abdelrasoul, Nader. "Optimization Techniques For an Artificial Potential Fields Racing Car Controller." Thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-6211.

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Context. Building autonomous racing car controllers is a growing field of computer science which has been receiving great attention lately. An approach named Artificial Potential Fields (APF) is used widely as a path finding and obstacle avoidance approach in robotics and vehicle motion controlling systems. The use of APF results in a collision free path, it can also be used to achieve other goals such as overtaking and maneuverability. Objectives. The aim of this thesis is to build an autonomous racing car controller that can achieve good performance in terms of speed, time, and damage level.

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Tanwir, Sarmad. "Online Techniques for Enhancing the Diagnosis of Digital Circuits." Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/82736.

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The test process for semiconductor devices involves generation and application of test patterns, failure logging and diagnosis. Traditionally, most of these activities cater for all possible faults without making any assumptions about the actual defects present in the circuit. As the size of the circuits continues to increase (following the Moore's Law) the size of the test sets is also increasing exponentially. It follows that the cost of testing has already surpassed that of design and fabrication. The central idea of our work in this dissertation is that we can have substantial savings in

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7

Storer, Jeremy J. "Computational Intelligence and Data Mining Techniques Using the Fire Data Set." Bowling Green State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1460129796.

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Hoori, Ammar O. "MULTI-COLUMN NEURAL NETWORKS AND SPARSE CODING NOVEL TECHNIQUES IN MACHINE LEARNING." VCU Scholars Compass, 2019. https://scholarscompass.vcu.edu/etd/5743.

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Accurate and fast machine learning (ML) algorithms are highly vital in artificial intelligence (AI) applications. In complex dataset problems, traditional ML methods such as radial basis function neural network (RBFN), sparse coding (SC) using dictionary learning, and particle swarm optimization (PSO) provide trivial results, large structure, slow training, and/or slow testing. This dissertation introduces four novel ML techniques: the multi-column RBFN network (MCRN), the projected dictionary learning algorithm (PDL) and the multi-column adaptive and non-adaptive particle swarm optimization t

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Kingry, Nathaniel. "Heuristic Optimization and Sensing Techniques for Mission Planning of Solar-Powered Unmanned Ground Vehicles." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1523874767812408.

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10

Abdussalam, Fathi M. A. "Antenna design using optimization techniques over various computaional electromagnetics. Antenna design structures using genetic algorithm, Particle Swarm and Firefly algorithms optimization methods applied on several electromagnetics numerical solutions and applications including antenna measurements and comparisons." Thesis, University of Bradford, 2018. http://hdl.handle.net/10454/17217.

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Dealing with the electromagnetic issue might bring a sort of discontinuous and nondifferentiable regions. Thus, it is of great interest to implement an appropriate optimisation approach, which can preserve the computational resources and come up with a global optimum. While not being trapped in local optima, as well as the feasibility to overcome some other matters such as nonlinear and phenomena of discontinuous with a large number of variables. Problems such as lengthy computation time, constraints put forward for antenna requirements and demand for large computer memory, are very com

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del, Valle Yamille E. "Optimization of power system performance using facts devices." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/29612.

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Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2010.<br>Committee Chair: Dr. Ronald G. Harley; Committee Member: Dr. Bonnie Heck; Committee Member: Dr. Deepak Divan; Committee Member: Dr. Ganesh K. Venayagamoorthy; Committee Member: Dr. Miroslav Begovic. Part of the SMARTech Electronic Thesis and Dissertation Collection.

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Srnec, Pavel. "Optimalizace nastavení závodního vozu simulátoru TORCS." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2012. http://www.nusl.cz/ntk/nusl-236557.

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This master's thesis is about nature optimalization technigues. Evolution algortihms together with main thesis topic, Particle Swarm Optimization, is introduced in the following chapter. Car setup and simulator TORCS are introduced in next chapter. Design and implementation are introduced in next chapters. Destination of t master's thesis is finding optimal car setups for different curcuits.

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Al-Olimat, Hussein S. "Optimizing Cloudlet Scheduling and Wireless Sensor Localization using Computational Intelligence Techniques." University of Toledo / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1403922600.

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Hassine, Hichem. "Modélisation, simulation et optimisation pour l'éco-fabrication." Thesis, Châtenay-Malabry, Ecole centrale de Paris, 2015. http://www.theses.fr/2015ECAP0016/document.

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Cette thèse se focalise sur la proposition et l’application des approches pour la modélisation de l’éco-fabrication. Ces approches permettent de préparer et simuler une démarche de fabrication des produits en assurant le couplage entre les objectifs écologiques et économiques.Les approches développées dans cette thèse sont basées sur les notions d’aide à la décision ainsi que l’optimisation multi objectifs. L’aide à la décision permet l’intervention en deux différents niveaux : le choix des impacts environnementaux à quantifier ainsi que le choix du scénario final de fabrication. Pour l’optimi

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Green, Robert C. II. "Novel Computational Methods for the Reliability Evaluation of Composite Power Systems using Computational Intelligence and High Performance Computing Techniques." University of Toledo / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1338894641.

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Devarakonda, SaiPrasanth. "Particle Swarm Optimization." University of Dayton / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1335827032.

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El, Dor Abbas. "Perfectionnement des algorithmes d'optimisation par essaim particulaire : applications en segmentation d'images et en électronique." Phd thesis, Université Paris-Est, 2012. http://tel.archives-ouvertes.fr/tel-00788961.

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La résolution satisfaisante d'un problème d'optimisation difficile, qui comporte un grand nombre de solutions sous-optimales, justifie souvent le recours à une métaheuristique puissante. La majorité des algorithmes utilisés pour résoudre ces problèmes d'optimisation sont les métaheuristiques à population. Parmi celles-ci, nous intéressons à l'Optimisation par Essaim Particulaire (OEP, ou PSO en anglais) qui est apparue en 1995. PSO s'inspire de la dynamique d'animaux se déplaçant en groupes compacts (essaims d'abeilles, vols groupés d'oiseaux, bancs de poissons). Les particules d'un même essai

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Al-kazemi, Buthainah Sabeeh No'man. "Multiphase particle swarm optimization." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available full text, 2002. http://wwwlib.umi.com/cr/syr/main.

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Tiporlini, Valentina. "Magnetocardiography in unshielded environment based on optical magnetometry and adaptive noise cancellation." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2013. https://ro.ecu.edu.au/theses/875.

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This thesis proposes and demonstrates the concept of a magnetocardiographic system employing an array of optically-pumped quantum magnetometers and an adaptive noise cancellation for heart magnetic field measurement within a magnetically-unshielded environment. Optically-pumped quantum magnetometers are based on the use of the atomic-spin-dependent optical properties of an atomic medium. An Mxconfiguration- based optically-pumped quantum magnetometer employing two sensing cells containing caesium vapour is theoretically described and experimentally developed, and the dependence of its sensitiv

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Scheepers, Christiaan. "Multi-guided particle swarm optimization : a multi-objective particle swarm optimizer." Thesis, University of Pretoria, 2017. http://hdl.handle.net/2263/64041.

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An exploratory analysis in low-dimensional objective space of the vector evaluated particle swarm optimization (VEPSO) algorithm is presented. A novel visualization technique is presented and applied to perform the exploratory analysis. The exploratory analysis together with a quantitative analysis revealed that the VEPSO algorithm continues to explore without exploiting the well-performing areas of the search space. A detailed investigation into the influence that the choice of archive implementation has on the performance of the VEPSO algorithm is presented. Both the Pareto-optimal front (PO

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Djaneye-Boundjou, Ouboti Seydou Eyanaa. "Particle Swarm Optimization Stability Analysis." University of Dayton / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1386413941.

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Zdráhal, Roman. "Planární antény se speciálními krycími vrstvami." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2008. http://www.nusl.cz/ntk/nusl-217690.

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This diploma thesis deals with the modeling of planar antennas with special superstrates in the CST Microwave Studio. Attention is given to the electromagnetic bandgap (EBG) substrates. Firstly, the working principle of these special substrates and generally physical phenomena accompanying electromagnetic waves propagation in a periodic medium are analyzed. By modeling of basic EBG structures in CST their dispersion diagrams were obtained and afterwards compared to one another. The object of the second part of this thesis was modeling of a chosen antenna in CST. An Antenna placed first on the

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Czogalla, Jens. "Particle swarm optimization for scheduling problems." Aachen Shaker, 2010. http://d-nb.info/1002307813/04.

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Jin, Nanbo. "Particle swarm optimization in engineering electromagnetics." Diss., Restricted to subscribing institutions, 2007. http://proquest.umi.com/pqdweb?did=1481677311&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Brits, Riaan. "Niching strategies for particle swarm optimization." Diss., Pretoria : [s.n.], 2002. http://upetd.up.ac.za/thesis/available/etd-02192004-143003.

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26

Lapizco-Encinas, Grecia C. "Cooperative Particle Swarm Optimization for Combinatorial Problems." College Park, Md.: University of Maryland, 2009. http://hdl.handle.net/1903/9901.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2009.<br>Thesis research directed by: Dept. of Computer Science. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.

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Yao, Wang. "Particle swarm optimization aided MIMO transceiver design." Thesis, University of Southampton, 2011. https://eprints.soton.ac.uk/301206/.

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In this treatise, we design Particle Swarm Optimization (PSO) aided MIMO transceivers. The employment of multiple antennas leads to the concept of multiple-input multiple-output (MIMO) systems, which constitute an effective way of achieving an increased capacity. When multiple antennas are employed at the Base Station (BS), it is possible to employ Multiuser Detection (MUD) in the uplink. However, in the downlink (DL), due to the size as well as power consumption constraints of mobile devices, so-called Multiuser Transmission (MUT) techniques may be employed at the BS for suppressing the multi

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Ojeda, Romero Juan Andre. "Dual Satellite Coverage using Particle Swarm Optimization." Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/50627.

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A dual satellite system in a Low Earth Orbit, LEO, would be beneficial to study the electromagnetic occurrences in the magnetosphere and their contributions to the development of the aurora events in the Earth's lower atmosphere. An orbit configuration is sought that would increase the total time that both satellites are inside the auroral oval. Some additional objectives include minimizing the total fuel cost and the average angle between the satellites' radius vectors. This orbit configuration is developed using a series of instantaneous burns applied at each satellite's perigee. An analysis

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Wilhelm, Paul Allan. "Pheromone particle swarm optimization of stochastic systems." [Ames, Iowa : Iowa State University], 2008.

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Urade, Hemlata S., and Rahila Patel. "Performance Evaluation of Dynamic Particle Swarm Optimization." IJCSN, 2012. http://hdl.handle.net/10150/283597.

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Optimization has been an active area of research for several decades. As many real-world optimization problems become increasingly complex, better optimization algorithms are always needed. Unconstrained optimization problems can be formulated as a D-dimensional minimization problem as follows: Min f (x) x=[x1+x2+……..xD] where D is the number of the parameters to be optimized. subjected to: Gi(x) <=0, i=1…q Hj(x) =0, j=q+1,……m Xε [Xmin, Xmax]D, q is the number of inequality constraints and m-q is the number of equality constraints. The particle swarm optimizer (PSO) is a relatively

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McNabb, Andrew W. "Parallel Particle Swarm Optimization and Large Swarms." BYU ScholarsArchive, 2011. https://scholarsarchive.byu.edu/etd/2480.

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Optimization is the search for the maximum or minimum of a given objective function. Particle Swarm Optimization (PSO) is a simple and effective evolutionary algorithm, but it may take hours or days to optimize difficult objective functions which are deceptive or expensive. Deceptive functions may be highly multimodal and multidimensional, and PSO requires extensive exploration to avoid being trapped in local optima. Expensive functions, whose computational complexity may arise from dependence on detailed simulations or large datasets, take a long time to evaluate. For deceptive or expensive o

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Xia, Gongyi. "Particle Swarm Optimization and Particle Filter Applied to Object Tracking." Thesis, North Dakota State University, 2016. https://hdl.handle.net/10365/27610.

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The particle filter is usually used as a tracking algorithm in non-linear under the Bayesian tracking framework. However, the problems of degeneracy and impoverishment degrade its performance. The particle filter is thereafter enhanced by evolutionary optimization, in particular, Particle Swarm Optimization (PSO) is used in this thesis due to its capability of optimizing non-linear problems. In this thesis, the PSO enhanced particle filter is reviewed followed by an analysis of its drawbacks. Then, a novel sampling mechanism for the particle filter is proposed. This method generates particles

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Lee, You-Jheng, and 李侑政. "An Integration of Particle Swarm Optimization Clustering Techniques for Collaborative Filtering." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/20235501748384583016.

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碩士<br>中原大學<br>資訊管理研究所<br>104<br>Recommender systems keep being innovated and improved as the amount of data increases significantly. Collaborative filtering recommender is now the mainstream of the personalized recommenders in recent years. The working principle is that, in a group of preference, a user and other members gather together for something or idea they love, and therefore there is a great chance that what is loved by the rest of the group is also loved by the user. The system automatically distributes the words of mouth to user A and those similar to user A, thus recommending produc

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Hung, Ho-Lung, and 洪珨隆. "Applications of Particle Swarm Optimization Technique on Wireless Communication Systems." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/95059377794308202668.

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博士<br>國立中正大學<br>電機工程所<br>95<br>In this dissertation, the applications of evolutionary algorithms on wireless communication systems are addressed. In recent years, evolutionary algorithms have been successfully applied to many fields. With the advantages of the capability in finding a global solution and dealing the nonlinear problems, we in this dissertation investigate the particle swarm optimization (PSO) technique in performance improvement for wireless communication systems. In the application to the optimum multiuser detection (OMUD) problem in code-division multiple-access (CDMA) and mul

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Ganjali, Afshar. "A Requirements-Based Partition Testing Framework Using Particle Swarm Optimization Technique." Thesis, 2008. http://hdl.handle.net/10012/4242.

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Modern society is increasingly dependent on the quality of software systems. Software failure can cause severe consequences, including loss of human life. There are various ways of fault prevention and detection that can be deployed in different stages of software development. Testing is the most widely used approach for ensuring software quality. Requirements-Based Testing and Partition Testing are two of the widely used approaches for testing software systems. Although both of these techniques are mature and are addressed widely in the literature and despite the general agreement on both of

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Lakide, Vedavrath. "Classification of Synthetic Aperture Radar Images using Particle Swarm Optimization Technique." Thesis, 2009. http://ethesis.nitrkl.ac.in/1438/1/VEDAVRATH_FINAL_PDF.pdf.

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In this thesis, SAR image classification problem is considered as an optimization problem various clustering techniques are addressed in literature for SAR image classification. This thesis focuses on an evolutionary based stochastic optimization technique that is Particle Swarm Optimization (PSO) technique for classification of SAR images. This technique composes of three main processes: firstly, selecting training samples for every region in the SAR image. Secondly, training these samples using PSO, and obtain cluster center of every region. Finally, the classification of SAR image with resp

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Kao, Pei-yuan, and 高培元. "Forecasting the TAIEX Based on Fuzzy Time Series, Particle Swarm Optimization Techniques and Support Vector Machines." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/67t828.

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碩士<br>國立臺灣科技大學<br>資訊工程系<br>100<br>In recent years, fuzzy time series has successfully been used to deal with forecasting problems. From the historical time series data, we can see that the slope of variation of each datum is an important to find the trend of fuzzy time series, where we can use the trend to forecast the variation of future. In this thesis, we present a new method to forecast the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) based on fuzzy time series, particle swarm optimization and support vector machines. In the proposed method, we first calculate the slop

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Zong-Lin, Liou, and 柳宗林. "The integration of dimensional reduction and Kmeans-Particle Swarm Optimization techniques on the landslide decision support system." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/86992677900952382316.

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碩士<br>嶺東科技大學<br>資訊科技應用研究所<br>97<br>The SDSS (Spatial Decision Support System) integrates GIS and the theory of Decision Support System. Numerous of past studies are focused on the statistical analysis. However, for a single event of landslide, this seems inadequate of understanding the observed factors to induce landslide. Thus, dimensional reduction becomes a feasible solution on information based techniques to handle the complexity on attributes of data on landslide. Accordingly, the present study used a hybrid model of K-means and Particle Swarm Optimization to resolve the complexity on the

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Hsu, San-li, and 徐三立. "Integration of Particle Swarm Optimization and Ant-inspired Search Techniques for Multi-Mode Resource-Constrained Project Scheduling." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/70631508178539112587.

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碩士<br>國立高雄第一科技大學<br>電腦與通訊工程研究所<br>100<br>In this study, the multi-mode resource-constrained project scheduling problem (MRCPSP) is considered. Without violating precedence and resource constraints, the goal in solving the MRCPSP is to achieve minimal total project duration. The MRCPSP is extremely complex and is known to be NP-hard in the strong sense. Due to the intractability of the problem, numerous research efforts have focused on particle swarm optimization (PSO) and ant colony optimization (ACO) to acquire satisfactory suboptimal solutions within a reasonable amount of computation cost.

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Dlamini, Thamie Khonzumthetho, and Thamie Khonzumthetho Dlamini. "Temperature forecasting based on weighted fuzzy relationship matrices and particle swarm optimization technique." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/2nb69j.

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碩士<br>國立臺北科技大學<br>電資國際專班<br>107<br>Song and Chissom proposed a fuzzy time series model consisting of two main procedures which were fuzzification plus the formation of fuzzy relationships resulting to forecasting of fuzzy time series. One research has pointed out that throughout the fuzzification method, different dimensions of intervals will result in numerous predicting results, and it has been suggested that the effective dimensions of intervals were used. The projecting results that were based on operative lengths of intervals were found to outclass those based on random ones. As the lengt

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PANDEY, PRASHANT. "APPLICATION OF PARTICLE SWARM OPTIMIZATION TECHNIQUE IN OPTIMAL LOCATION AND SIZING OF SVC." Thesis, 2013. http://dspace.dtu.ac.in:8080/jspui/handle/repository/15674.

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As economy grows, the demand of power increases. The increase in the reactive power demand may cause worsening in the voltage profile. To ensure the reliable power supply and to reduce the losses, reactive power compensation is required. For reactive power compensation fact devices can be used. Here the Static Var Compensator (SVC) is taken as a case as shunt fact device. In this thesis, optimal placement and sizing of SVC considering the bus voltages and cost of installation has been formulated using stochastic approach. The non-inferior set has been generated for IEEE 14-bus systems us

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Manalu, Gandhi Maruli Tua, and 王感天. "Fuzzy Forecasting Based on Two-Factors High-Order Fuzzy-Trend Logical Relationship Groups and Particle Swarm Optimization Techniques." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/61261713981055899173.

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碩士<br>國立臺灣科技大學<br>資訊工程系<br>99<br>Fuzzy time series have been widely used in solving forecasting problem, such as the enrollments forecasting, the temperature forecasting, the stock index forecasting, the exchange rates forecasting, …, etc. Particle swarm optimization is a swarm-based optimization method that can find a near optimal solution for any kind of optimization problems. Therefore, if we can use it appropriately to determine the optimal proportion of the data in the current dates in calculating the data in the next date, we can get a nearly-optimal solution. In this thesis, we present

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Kao, I.-Wei, and 高逸瑋. "A Hybrid Data Clustering Technique based Nelder-Mead Simplex Method and Particle Swarm Optimization." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/10012015761375398798.

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碩士<br>聖約翰科技大學<br>自動化及機電整合研究所<br>94<br>Data clustering helps one discern the structure of and simplify the complexity of massive quantities data. It.is a common technique for statistical data analysis, and it is used in many fields, including machine learning, data mining, pattern recognition, image analysis and bioinformatics, in which the distribution of information can be of any size and shape. The well-known K-means algorithm, which has been successfully applied to many practical clustering problems, suffers from several drawbacks due to its iterative nature. A hybrid technique based on K-m

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chen, meng-tso, and 陳孟佐. "A Hybrid Data Clustering Technique based on Hierarchical Genetic Algorithm and Particle Swarm Optimization." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/47687311750154952010.

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碩士<br>樹德科技大學<br>資訊管理研究所<br>92<br>Recently, the data cluster discussion topics are focused on the following three point, (1)to improve the efficiency of cluster algorithm, (2)to search the most appropriate cluster quantity, (3)to distribute data in right cluster. Presently, research target is focused mainly on immobile cluster number, to allot the data to the right cluster and the rest will search cluster number. This dissertation emphasizes on the automatic search of cluster number and appropriate data distribution in the group. In the paper, a hybrid data clus

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Huang, Li-Chuan, and 黃浰娟. "Applying the Particle Swarm Optimization Technique to the Resource-Constrainted Multi-Project Scheduling Problem." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/93532696600919722297.

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碩士<br>國立屏東科技大學<br>工業管理系<br>94<br>The main purpose of this study is introduce the particle swarm optimization (PSO)-based approach to solve the resource-constrained multi-project scheduling problem (RCMPSP) with the objectives of maximizing the total project net present value (NPV) and minimizing the total project delay. The RCMPSP has attracted many researchers during the last years. Since it is an NP-hard problem, different kinds of heuristics for it have been proposed. PSO is an evolutionary optimization technique that simulates the social behavior of bird flocking to desired places. It has

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Agbugba, Emmanuel Emenike. "Hybridization of particle Swarm Optimization with Bat Algorithm for optimal reactive power dispatch." Diss., 2017. http://hdl.handle.net/10500/23630.

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This research presents a Hybrid Particle Swarm Optimization with Bat Algorithm (HPSOBA) based approach to solve Optimal Reactive Power Dispatch (ORPD) problem. The primary objective of this project is minimization of the active power transmission losses by optimally setting the control variables within their limits and at the same time making sure that the equality and inequality constraints are not violated. Particle Swarm Optimization (PSO) and Bat Algorithm (BA) algorithms which are nature-inspired algorithms have become potential options to solving very difficult optimization problem

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Chien, Chih-Yao, and 簡誌垚. "Solving the Traveling Salesman Problem Based on Genetic Algorithms, Ant Colony System, Particle Swarm Optimization and Simulated Annealing Techniques." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/90253115442554565550.

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碩士<br>國立臺灣科技大學<br>資訊工程系<br>98<br>The traveling salesman problem is an important research topic. In the traveling salesman problem, a traveling salesman wants to travel all cities and each city only can be visited once. The problem is to minimize the distance of the complete route in which the salesman takes. In this thesis, we present two new methods for solving the traveling salesman problem using the genetic algorithms, ant colony system, particle swarm optimization and the simulated annealing algorithm. In the first method, we present a new method combining the genetic algorithms and the an

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Li, Ying-Hao, and 李英濠. "Development of a New Iterative Learning Controller Based on Particle Swarm Optimization Approach and Adaptive Frequency Bandwidth Adjusting Techniques." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/97535153711064019881.

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碩士<br>國立彰化師範大學<br>機電工程學系<br>100<br>This thesis utilizes the Improved Particle Swarm Optimization (IPSO) technique with bounded constraints for adjusting the gains of a Proportional-Integral-Derivative (PID) controller and Iterative Learning Control (ILC) controller and zero phase Butterworth Low-Pass Filter bandwidth. This study first compares the conventional ILC-PID controller with proposed IPSO-ILC-PID controller, and then compares the fixed bandwidth of IPSO-ILC-PID controller with proposed adjusting bandwidth method with IPSO-ILC-PID controller. A cycloid trajectory for simulation the rea

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Khan, S. A. (Salman Ahmad). "Design and analysis of evolutionary and swarm intelligence techniques for topology design of distributed local area networks." Thesis, 2009. http://hdl.handle.net/2263/28233.

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Topology design of distributed local area networks (DLANs) can be classified as an NP-hard problem. Intelligent algorithms, such as evolutionary and swarm intelligence techniques, are candidate approaches to address this problem and to produce desirable solutions. DLAN topology design consists of several conflicting objectives such as minimization of cost, minimization of network delay, minimization of the number of hops between two nodes, and maximization of reliability. It is possible to combine these objectives in a single-objective function, provided that the trade-offs among these objecti

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Tu, Po-Hsien, and 杜柏憲. "Maximum Power Point Tracking of Photovoltaic Systems with Modified Particle Swarm Optimization Technique Under Partial-Shading Conditions." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/38051014257635357920.

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碩士<br>國立暨南國際大學<br>電機工程學系<br>104<br>The major target of this thesis is to develop the maximum power tracker of photovoltaic (PV) systems under the partial-shading conditions. Since the weather is unpredictable, there might exist local and global maximum power points (MPP) in the systems. Therefore, we must be able to track the global MPP under the partial-shading conditions in order to make our PV systems offer effective maximum power output for obtaining optimal system performance. First of all, the mathematical model is established for a PV array system to investigate and analyze the voltage

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