Results 31 to 40 of about 5,023,817 (336)

A self-learning particle swarm optimizer for global optimization problems [PDF]

, 2011
Copyright @ 2011 IEEE. All Rights Reserved. This article was made available through the Brunel Open Access Publishing Fund.Particle swarm optimization (PSO) has been shown as an effective tool for solving global optimization problems.
Yang, S, Li, Changhe, Nguyen, T. T., null Changhe Li, null Shengxiang Yang, Nguyen, T T, Yang, Shengxiang, Li, C, null Trung Thanh Nguyen   +8 more
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Orthogonal learning particle swarm optimization [PDF]

, 2010
Particle swarm optimization (PSO) relies on its learning strategy to guide its search direction. Traditionally, each particle utilizes its historical best experience and its neighborhood’s best experience through linear summation.
Zhi-hui Zhan, Jun Zhang, Yu-hui Shi, Zhan, Z-H., Yun Li, Li, Y., Shi, Y-H., Zhang, J.   +7 more
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A particle swarm optimization based memetic algorithm for dynamic optimization problems [PDF]

, 2010
Copyright @ Springer Science + Business Media B.V. 2010.Recently, there has been an increasing concern from the evolutionary computation community on dynamic optimization problems since many real-world optimization problems are dynamic.
Wang, H, Yang, S, Wang, Dingwei, Hongfeng Wang, Shengxiang Yang, W. H. Ip, Ip, W. H., Dingwei Wang, Yang, Shengxiang, Wang, Hongfeng, Ip, WH, Wang, D   +11 more
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Stock Prediction Model Based on Mixed Fractional Brownian Motion and Improved Fractional-Order Particle Swarm Optimization Algorithm

Fractal and Fractional, 2022
As one of the main areas of value investing, the stock market attracts the attention of many investors. Among investors, market index movements are a focus of attention.
Hongwen Hu, Chunna Zhao, Jing Li, Yaqun Huang   +3 more
doaj   +1 more source

Feedback learning particle swarm optimization [PDF]

, 2011
This is the author’s version of a work that was accepted for publication in Applied Soft Computing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may ...
Tang, Y, Zidong Wang, Wang, Z, Yang Tang, Fang, J, Jian-an Fang   +5 more
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An improved search ability of particle swarm optimization algorithm for tracking maximum power point under shading conditions

Electrical engineering & Electromechanics, 2022
Introduction. Extracting maximum possible power from solar energy is a hot topic of the day as other sources have become costly and lead to pollution. Problem.
H. Saeed, T. Mehmood, F. A. Khan, M. S. Shah, M. F. Ullah, H. Ali   +5 more
doaj   +1 more source

Particle swarm optimization with composite particles in dynamic environments [PDF]

, 2010
This article is placed here with the permission of IEEE - Copyright @ 2010 IEEEIn recent years, there has been a growing interest in the study of particle swarm optimization (PSO) in dynamic environments.
Yang, S, Yang, Shengxiang, Wang, D, Liu, L   +3 more
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A dynamic adaptive particle swarm optimization and genetic algorithm for different constrained engineering design optimization problems

Advances in Mechanical Engineering, 2019
A dynamic adaptive particle swarm optimization and genetic algorithm is presented to solve constrained engineering optimization problems. A dynamic adaptive inertia factor is introduced in the basic particle swarm optimization algorithm to balance the ...
Hao Zhu, Yumei Hu, Weidong Zhu
doaj   +1 more source

Swarming genetic algorithm: A nested fully coupled hybrid of genetic algorithm and particle swarm optimization.

PLoS ONE, 2022
Particle swarm optimization and genetic algorithms are two classes of popular heuristic algorithms that are frequently used for solving complex multi-dimensional mathematical optimization problems, each one with its one advantages and shortcomings ...
Panagiotis Aivaliotis-Apostolopoulos, Dimitrios Loukidis   +1 more
doaj   +1 more source

A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

, 2015
Particle swarm optimization (PSO) is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques. This survey presented a comprehensive investigation of PSO.
Yudong Zhang, Shuihua Wang, G. Ji
semanticscholar   +1 more source