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Dissertations / Theses on the topic 'Modified particle searm optimization'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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1

Alrasheed, Mohammed R. A. "A modified particle swarm optimization and its application in thermal management of an electronic cooling system." Thesis, University of British Columbia, 2011. http://hdl.handle.net/2429/37900.

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Particle Swarm Optimization (PSO) is an evolutionary computation technique, which has been inspired by the group behavior of animals such as schools of fish and flocks of birds. It has shown its effectiveness as an efficient, fast and simple method of optimization. The applicability of PSO in the design optimization of heat sinks is studied in this thesis. The results show that the PSO is an appropriate optimization tool for use in heat sink design.PSO has common problems that other evolutionary methods suffer from. For example, in some cases premature convergence can occur where particles ten

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Wei, Xing. "Optimization of Strongly Nonlinear Dynamical Systems Using a Modified Genetic Algorithm With Micro-Movement (MGAM)." DigitalCommons@USU, 2009. https://digitalcommons.usu.edu/etd/450.

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The genetic algorithm (GA) is a popular random search and optimization method inspired by the concepts of crossover, random mutation, and natural selection from evolutionary biology. The real-valued genetic algorithm (RGA) is an improved version of the genetic algorithm designed for direct operation on real-valued variables. In this work, a modified version of a genetic algorithm is introduced, which is called a modified genetic algorithm with micro-movement (MGAM). It implements a particle swarm optimization(PSO)-inspired micro-movement phase that helps to improve the convergence rate, while

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Zemzami, Maria. "Variations sur PSO : approches parallèles, jeux de voisinages et applications Application d’un modèle parallèle de la méthode PSO au problème de transport d’électricité A modified Particle Swarm Optimization algorithm linking dynamic neighborhood topology to parallel computation An evolutionary hybrid algorithm for complex optimization problems Interoperability optimization using a modified PSO algorithm A comparative study of three new parallel models based on the PSO algorithm Optimization in collaborative information systems for an enhanced interoperability network." Thesis, Normandie, 2019. http://www.theses.fr/2019NORMIR11.

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Reconnue depuis de nombreuses années comme une méthode efficace pour la résolution de problèmes difficiles, la méta-heuristique d’optimisation par essaim de particules PSO (Particle Swarm Optimization) présente toutefois des inconvénients dont les plus étudiés sont le temps de calcul élevé et la convergence prématurée. Cette thèse met en exergue quelques variantes de la méthode PSO visant à échapper à ces deux inconvénients de la méthode. Ces variantes combinent deux approches : la parallélisation de la méthode de calcul et l’organisation de voisinages appropriés pour les particules. L’évaluat

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Li, Nai-Jen, and 黎乃仁. "Weighted Particle Based Modified Particle Swarm Optimization and Its Applications." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/75030636258994420520.

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博士<br>國立中央大學<br>電機工程學系<br>103<br>This dissertation proposes weighted particle based modified particle swarm optimization (PSO) and its applications. The weighted particle is composed of personal best particles with their best objective value (minimal value), and the weighted particle can provide better opportunity getting closer to the optimal solution. Based on weighted particle, this dissertation proposes three modified algorithms. One is an enhanced particle swarm optimization with weighted particle (EPSOWP) which has two search behaviors of local search and global search so that the swarm

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Wang, Ya-shyan, and 王雅賢. "Research on a Modified Particle Swarm Optimization Algorithm." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/62188914837148750779.

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碩士<br>中原大學<br>資訊管理研究所<br>94<br>Particle Swarm Optimization (PSO), an algorithm with the concept of swarm intelligence, also a new branch in evolutionary computing, possesses the merits of fast converging, as well as the simplification in parameter setting. Nevertheless, PSO has the demerit of the inclination to trap into local optima because when particles move, they merely follow pbest and gbest .Although the standard PSO algorithm and other modified algorithms has attempted to enhance the efficiency in utilizing a swarm to search global best, they still fail in avoiding particles falling int

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Liao, Chun-Ming, and 廖俊明. "Applying Modified Particle Swarm Optimization for Finding Motif." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/97787732133655995979.

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碩士<br>義守大學<br>工業工程與管理學系碩士班<br>98<br>Remarkable advances on human genome project and the molecular biology provide availability of genome-wide gene expression data. Gene activity and regulation mechanism is often affected by binding transcription factors to short fragments in DNA sequences called motifs. The motif is significant pattern of letters (nucleotides, amino acids) contained within long sequences. Identification of subtle regulatory motifs in a DNA or protein sequence is a difficult pattern recognition problem in genetics. Motif finding is also an important area of multiple sequence al

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Li, Jung-Chieh, and 李榮結. "Modified Particle Swarm Optimization for High Dimensional Problems." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/69494731072811920445.

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碩士<br>國立臺灣海洋大學<br>商船學系所<br>99<br>The difficulty to solve a high dimensional optimization problem will be much more than low dimensional problems due to the increasing of solution space. The Particle Swarm Optimization (PSO) has been applied extensively to various fields.. However, there are weaknesses in adopting PSO in high dimensional problems. For examples, PSO is easily trapped into local extreme resulting in low optimizing precision or failure, and even though in the surroundings of extreme solution, the rate of convergence need to be improved. This study is focused on the performance o

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Ying-Ju, Ho. "Construct D-Optimal Designs Using Modified Particle Swarm Optimization." 2006. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0009-2607200615310300.

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Ho, Ying-Ju, and 何英如. "Construct D-Optimal Designs Using Modified Particle Swarm Optimization." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/49523377318970366187.

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碩士<br>元智大學<br>工業工程與管理學系<br>94<br>Optimal designs are applied extensively to the process industry. Asymmetrical designs are now widely used in practice since many engineering problems usually involve complex objective functions and several constraints simultaneously. Hence, the classical designs cannot be valid for this circumstance any more. Accordingly, computer-generated designs are the legitimate choice for situations where standard factorial, fractional factorial designs or response surface designs cannot be easily employed. Design optimality criteria are characterized by letters of the al

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Yi-Yin, Chiu. "Modified Particle Swarm Optimization for Solving the Global Optimization of Continuous Multimodal Functions." 2004. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0009-0112200611323569.

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(10725597), Omkar Mahesh Parkar. "Multi-Objective Optimization of Plug-in HEV Powertrain Using Modified Particle Swarm Optimization." Thesis, 2021.

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Increase in the awareness environmental conservation is leading the automotive industry into the adaptation of alternatively fueled vehicles. Electric, Fuel-Cell as well as Hybrid-Electric vehicles focus on this research area with aim to efficiently utilize vehicle powertrain as the first step. Energy and Power Management System control strategies play vital role in improving efficiency of any hybrid propulsion system. However, these control strategies are sensitive to the dynamics of the powertrain components used in the given system. A kinematic mathematical model for Plug-in Hybrid Electri

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Parkar, Omkar. "Multi-Objective Optimization of Plug-In HEV Powertrain Using Modified Particle Swarm Optimization." Thesis, 2021. http://dx.doi.org/10.7912/C2/15.

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Indiana University-Purdue University Indianapolis (IUPUI)<br>An increase in the awareness of environmental conservation is leading the automotive industry into the adaptation of alternatively fueled vehicles. Electric, Fuel-Cell as well as Hybrid-Electric vehicles focus on this research area with the aim to efficiently utilize vehicle powertrain as the first step. Energy and Power Management System control strategies play a vital role in improving the efficiency of any hybrid propulsion system. However, these control strategies are sensitive to the dynamics of the powertrain components used in

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Yi-Yin, Chiu, and 邱怡瑛. "Modified Particle Swarm Optimization for Solving the Global Optimization of Continuous Multimodal Functions." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/42490178787854981603.

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碩士<br>元智大學<br>工業工程與管理學系<br>92<br>The development of the Particle Swarm Optimization (PSO) has been almost ten years since 1995. From that time on, a variety of modifications of the original PSO has been proposed by many PSO researchers. The evolutionary concept of PSO, simple in concept, easy to implement and computational efficient, is partly the motivation of this thesis. The performance of the original PSO on the solution quality and convergence speed becomes much aggravated while optimizing multimodal functions with higher dimension. This is the main objective of this research such that we

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Wu, Chih-Jyz, and 吳昌志. "Modified Particle Swarm Optimization Algorithms for the Traveling Salesman Problem." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/20600614853314927681.

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碩士<br>中原大學<br>資訊管理研究所<br>95<br>According Particle Swarm Optimiztion Algorithm, is an swarm intelligence Algorithm. Throught simulate birds behavior,each particle share information each other to reach the best result. But the Particle Swarm Optimiztion Algorithm is good at the continue function,be bad at discrete function. For proofing then Particle Swarm Optimiztion Algorithm can be used at discrete problem, this article combine Particle Swarm Optimiztion Algorithm with 2-Opt algorithm and Greed mtheod to slove Traveling salesman problem. The performance would be superior then the original al

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Chuang, Kai-Chih, and 莊凱智. "Applying Modified Particle Swarm Optimization to the Traveling Salesman Problem." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/33578697595647658191.

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碩士<br>國立高雄應用科技大學<br>工業工程與管理系<br>99<br>Solving traveling salesman problem is used by integer programming which often costs a lot of computation time following an exponential growth in the larger size problem. It is an inefficient situation. Therefore, in order to enhance the efficiency of exploring solutions, heuristic algorithms become important and well-known methods to use, such as particle swarm optimization, genetic algorithm, tabu search, simulated annealing, ant colony optimization. In this study, we use particle swarm algorithm to find a feasible solution, and then use the genetic alg

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Juang, Chi-Yuan, and 莊啟元. "Artificial Neural Networks Design Based On Modified Adaptive Particle Swarm Optimization." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/4cf39q.

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碩士<br>國立高雄應用科技大學<br>電子工程系<br>97<br>In this thesis, the weights of the artificial neural networks (ANN) are trained by modified adaptive particle swarm optimization (MAPSO). Back-propagation (BP) is an approximate steepest descent algorithm, but BP often finds the local optimal solution not the global optimal solution, because of the initial weights. The particle swarm optimization (PSO) method is one of the most powerful methods for letting the entire individuals move to the target, hence it can avoid to get the local optimal solution. However, the parameters, which greatly influence the algo

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Tang, Jia-Ci, and 唐家麒. "Research on Artificial Neural Network Training Using Modified Particle Swarm Optimization." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/xe6ame.

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碩士<br>義守大學<br>電機工程學系<br>105<br>In this research, the modified particle swarm optimization algorithm will be applied to the training of artificial neural networks for machine learning problems. This modified algorithm appropriately combines the standard particle swarm optimization and Lévy flight (very often used in cuckoo search algorithm) in order to escape from the local minima of the cost surface and to avoid the premature convergence of the candidate solutions. Three numerical examples will be used to illustrate the use of our proposed algorithm. Some comparisons of the performances usi

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Chen, Ming-Hong, and 陳銘鴻. "Using the modified particle swarm optimization to identify the mechanical systems." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/71086261905320118909.

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碩士<br>高苑科技大學<br>電子工程研究所<br>100<br>Artificial intelligence is once of the most popular optimization algorithms. This dissertation focuses on developing a optimization and optimal control theory. Several solution searching strategies and mechanisms are proposed to improve solution searching capability and efficiency of population-based optimizers for dealing with different types of optimization problems. To verify the solution searching ability in the solution space, the proposed algorithm will be applied to mechanism systems. This study mainly proposes an efficient modified particle swarm optim

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Hwang, Yu-Shou, and 黃郁授. "A Study on Modified Particle Swarm Optimization by Adaptive Inertia Weight." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/48023324886567333080.

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碩士<br>中原大學<br>資訊管理研究所<br>95<br>Particle Swarm Optimization Algorithm (PSO) is a new technology in evolution computing. PSO has many advantages, such as fewer parameters needed to be adjusted and the rapid convergence speed. It is the same as Ant Colony Optimization Algorithm. PSO finds the best solution by studying the nature. In addition to study birds and fishes forage, PSO also join the human social science. Each particle is following personal best solution and global solution when moving. Each particle computes new flying location to find the best answer by searching pbest and gbest after

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Chen, Chun-Jen, and 陳俊仁. "The PID Controller Design based on Modified Particle Swarm Optimization Method." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/63176645305540303924.

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碩士<br>國立高雄海洋科技大學<br>輪機工程研究所<br>99<br>In this research, the modified particle swarm optimization method (PSO) is investigated. The traditional particle swarm optimization method was bringing the local minimum characteristic. Consequently, the genetic algorithm (GA) is cooperating with the particle swarm optimization method to avoid the local minimum characteristic. The basic elements, including distribution, selection and mutation will count into the particle swarm optimization method based on constrict factor. There are three benchmark problems and two control systems be used to verify the pro

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Lin, Wu-Cheng, and 林武鉦. "Voltage Stability Study for Dynamic Load with Modified Orthogonal Particle Swarm Optimization." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/42482696909114738763.

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碩士<br>國立中山大學<br>電機工程學系研究所<br>99<br>The thesis use capacitors, Static Synchronous Compensator (STATCOM) and wind generator to get optimal voltage stability for twenty-four-hour dynamic load by compensating real/reactive power. In the thesis, Modified Orthogonal Particle Swarm Optimizer (MOPSO) is proposed to find the sitting and sizing of capacitors, STATCOM and wind generator, and integrate Equivalent Current Injection (ECI) algorithm to solve Optimal Power Flow (OPF) to achieve optimal voltage stability. The algorithm uses MOPSO to renew STATCOM and wind turbine sizing Gbest with multiple cho

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Lin, Shih-Yu, and 施育霖. "A Modified Particle Swarm Optimization Based on Gird Method for Optimization Design of Spring of Slider Phone." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/25293537176964803279.

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碩士<br>國立臺灣海洋大學<br>系統工程暨造船學系<br>99<br>In this research, a numerical population-based optimization algorithm is developed for optimization problems, the algorithm is established based on the particle swarm optimization incorporated with the grid method. To verify the proposed algorithm, we selected 11 benchmark functions, with variables interacted or non- interacted. Meantime, there are three different number of dimensions for each tested functions are considered, they are 30, 50 and 100 respectively. The results obtained by the proposed method are shown much improved than those from the pa

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Chuang, Cheng-Hsueh, and 莊承學. "The Resolution of Overlapping Autofluorescence Spectrum Using A Modified Particle Swarm Optimization Algorithm." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/76022545424235903050.

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碩士<br>國立高雄大學<br>電機工程學系碩士班<br>99<br>In this thesis, we take an improved particle swarm optimization algorithm for the separation of overlapping spectra where the speed update is the major improvement. Taking advantage of the concepts of inertia factor and constriction coefficient in the proposed algorithm, the convergence rate and the accuracy are significant improved. In the experiments, we used an optical Y-type fiber to conduct excitation light from the 337-nm nitrogen laser (VSL-337ND-S, LSI) to irradiate on the skin surface so that we could get an excitation fluorescence signal with the w

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Yu, Hong-Kuan, and 余泓寬. "Investigation of the Digital Image Stabilization Based on Modified Particle Swarm Optimization Algorithm." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/08971462378076036972.

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碩士<br>國立臺灣海洋大學<br>通訊與導航工程學系<br>101<br>General camera while shooting, because of manpower jitter, car driving Britain slope vibration, wind blowing, and other external interference leaving the shooting out of the image sequence will produce unwanted jitter. This thesis intends to propose a digital PI-based digital image stabilization technology to remove unwanted jitter effect such that the authenticity of the original image can be preserved. Proposed image stabilization technology includes the global mobile vector (the motion vector estimation unit) and the motion compensation vector (the moti

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Ho, Ming-Hui, and 何銘輝. "Solution to vehicle routing problem with time window based on modified particle swarm optimization." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/00235499772254922261.

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碩士<br>國立金門大學<br>電子工程學系碩士班<br>101<br>The vehicle routing problem applied in such fields as the flow of goods , factory scheduling and management has been widely researched by scholars, and is gradually put to practical use in our daily life. Therefore, it is of great value to find solutions to the vehicle routing problems so as to lower costs. 　　This paper proposes the particle swarm optimization (PSO) to solve the vehicle routing problem with time windows(VRPTW) , and hybrid genetic algorithm (GA) and hill-climbing Algorithm (HC) characteristics of particle expression to construct the vehicle

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Liu, Hsueh-Chien, and 劉學謙. "Maximum Power Point Tracking Method Based on Modified Particle Swarm Optimization for Photovoltaic Systems." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/66429997649339210680.

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碩士<br>國立勤益科技大學<br>電機工程系<br>103<br>This study investigated the output characteristics of photovoltaic module arrays with partial module shading. Accordingly, we presented a maximum power point tracking (MPPT) method that can effectively track the global optimum of multi-peak curves. This method was based on particle swarm optimization (PSO). The concept of linear decreases and slope in weighting was added to improve the tracking performance of the maximum power point tracker. First, the Matlab software was used for to simulation,then the PIC single chip was adopted to implement the MPPT for sin

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Mejia, Victor David Lopez, and 洪衛德. "A Modified Binary Particle Swarm Optimization Algorithm to Solve the Thermal Unit Commitment Problem." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/mrmzpc.

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碩士<br>國立中山大學<br>電機電力工程國際碩士學程<br>106<br>The last two decades have seen the advent of metaheuristic-based methods to solve both continuous and discrete optimization problems. While there are many paradigms available, the Particle Swarm Optimization (PSO) algorithm has had a profound impact in the mathematical optimization field. Extensive efforts, often with good results, have been made in the literature to improve the performance of the PSO algorithm by modifying the inertia weight, the position, and the velocity update equations. While these equations are still fundamental in its discrete coun

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Yang, Bin [Verfasser]. "Modified particle swarm optimizers and their application to robust design and structural optimization / Bin Yang." 2009. http://d-nb.info/99460453X/34.

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Cheng, Chiu-Chun, and 鄭秋君. "Application of Modified Particle Swarm Optimization Algorithm to Multi-user Detection in DS-UWB System." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/5775da.

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碩士<br>國立臺北科技大學<br>電機工程系所<br>95<br>For the multi-user application, the multiple access interference (MAI) due to imperfect orthogonality between spreading codes induced by UWB dense multi-path degrades system performance. Though optimum multi-user detector (OMD) can achieve remarkable performance, its computational complexity is too high to implement. Therefore, many sub-optimal multi-user detectors (MUDs) have been proposed to attain best trade-off between performance and complexity, such as Genetic algorithm-based multi-user detector (GA-MUD). However, BER performance of GA-MUD is not good en

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Wang, X., G. Zhang, J. Zhao, H. Rong, F. Ipate, and Raluca Lefticaru. "A modified membrane-inspired algorithm based on particle swarm optimization for mobile robot path planning." 2015. http://hdl.handle.net/10454/17606.

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Yes<br>To solve the multi-objective mobile robot path planning in a dangerous environment with dynamic obstacles, this paper proposes a modified membraneinspired algorithm based on particle swarm optimization (mMPSO), which combines membrane systems with particle swarm optimization. In mMPSO, a dynamic double one-level membrane structure is introduced to arrange the particles with various dimensions and perform the communications between particles in different membranes; a point repair algorithm is presented to change an infeasible path into a feasible path; a smoothness algorithm is proposed

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Juang, Yi-Ruei, and 莊佾叡. "Application of Modified Particle Swarm Optimization Algorithms to Multi-user Detection in Uplink MIMO-OFDM Systems." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/dt8zeh.

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碩士<br>國立臺北科技大學<br>電機工程系所<br>97<br>This study applies modified particle swarm optimization (PSO) algorithms to MIMO-OFDM uplink systems for multiuser detection. Multiuser interference (MUI) is a major factor that degrades system performance. To overcome this problem, optimal multiuser detector (OMD) is recognized as the best solution, but its computational complexity is too high to be implemented for practical applications. To achieve a best compromise between system performance and complexity, many suboptimal detectors, such as genetic algorithm-based multiuser detector (GA-based MUD), have be

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Xu, Shao-Hong, and 徐韶鴻. "Design of Fractional-Order PID Controller for a Fractional Order Systems Using Modified Particle Swarm Optimization Approach." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/4t826t.

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碩士<br>國立高雄應用科技大學<br>電機工程系博碩士班<br>103<br>A optimal Fractional Order controller design problem is studied in this thesis, the particle swarm optimization method is used to search the best parameters of the FO controllers. Among different particle swarm optimization methods, this study shows the one with time-varying acceleration coefficients and time-varying intertia weight could result in a smallest performance index, The result show that the modified PSO method is highly suitable for the searching for optimal controller parameters of the FO systems.

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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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鄭鈺暉. "Antenna Selection and Power Allocation in MIMO systems :A Cooperative Scheme based on modified Genetic Algorithms and Particle Swarm Optimization." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/92043549350091166398.

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碩士<br>國立臺灣海洋大學<br>電機工程學系<br>100<br>ABSTRACT MIMO antenna systems can increase data transmission rate and reliability, but also require larger hardware cost and computational complexity. To reduce hardware cost while maintaining the merits of data rate and reliability, this thesis considers a hybrid system with space-time encoding and spatial multiplexing, under which the joint antenna selection and power allocation problem is solved by maximizing the channel capacity subjected to a fixed total transmission power. To achieve this goal, we propose a cooperative method that uses the priorit

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Boeringer, Daniel Wilharm. "Multi-objective particle swarm optimization of a modified Bernstein polynomial for curved phased array synthesis using Bézier curves, surfaces, and volumes." 2004. http://etda.libraries.psu.edu/theses/approved/WorldWideIndex/ETD-583/index.html.

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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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