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A mini tutorial about Particle swarm optimization
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Particle swarm optimization (PSO) was originally designed and introduced by Eberhart and
Kennedy (Ebarhart, Kennedy, 1995 Kennedy, Eberhart, 1995 Ebarhart, Kennedy, 2001). The
PSO is a population based search algorithm based on the simulation of
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one of the most optimization techniques known is the particle swarm optimization tech
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采用粒子群算法的参数辨识，计算速度更快，参数更准确。-Using particle swarm optimization algorithm parameter identification, computing faster, more accurate parameters.
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That is dicument talkin about network training function that updates weight and bias values according to particle swarm optimization.
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Swarm based text summarization, extraction sentence by using particle swarm optimization
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Data clustering using particle swarm optimization Data clustering using particle swarm optimization
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K-means Algorithm Based on Particle Swarm
Optimization Algorithm for Anomaly Intrusion Detection
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During the last decade, many variants of the original
particle swarm optimization (PSO) algorithm have been
proposed. In many cases, the difference between two variants can
be seen as an algorithmic component being present in one variant
but
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c sharp particle swarm optimization
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我在IEEE下载的文章，关于标准PSO算法改进的，感觉挺经典的一篇文章，希望对大家有好处。-An adaptive particle swarm optimization (APSO)
that features better search efficiency than classical particle swarm
optimization (PSO) is presented
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A Hybrid Chaos-Particle Swarm Optimization Algorithm for the
Vehicle Routing Problem with TimeWindow
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本文提出了一种新的混合模糊动态速度反馈的粒子群的优化(HFDVF-PSO）解决经济调度问题的非光滑的成本考虑阀点效应和多种燃料选择功能。-This paper proposes a new Hybrid Fuzzy Dynamic Velocity Feedback Particle Swarm Optimization (HFDVF-PSO) for solving conomic Dispatch (ED) problem with non-smooth cost functions con
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有关粒子群优化算法的，自己整理！word里含有matlab程序说明-For particle swarm optimization, and organize their own! word descr iption contains matlab program
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粒子群优化算法，外文的，学习粒子群算法的-PSO, a foreign language, learning PSO
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A new method to improve the Particle Swarm
Optimization using Cellular Learning Automata
(CLAPSO)
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摘要：新型元启发式算法例如粒子群算法，萤火虫算法，和声搜索算法已经成为现今复杂的优化问题的有效解决方法。该文基于蝙
蝠的回声定位行为提出了一种新型的元启发式算法———蝙蝠算法，同时也将现有的一些算法的优点引入到该算法中。 改文对该算
法进行了详细的公式化表述并对其执行流程的作出了说明，并且将该算法与遗传算法、粒子群优化算法等算法进行了比较。仿真结
果表明,蝙蝠算法明显优于其他算法，并对进一步的研究作出了展望。-Summary: The new meta-heuristic algor
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基于改进负荷密度法的微网负荷预测_王有春，基于改进粒子群算法的微网环保经济运行的优化_万术来，基于改进型快速寻优算法的微网经济负荷优化_胡龙龙_温向宇_黄焯麒-Improved load density law microgrid load forecasting based on _ Wang Youchun, based on improved particle swarm optimization algorithm Microgrid green economy run _ Wan su
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In this paper, we present a new algorithm of swarm intelligence,
namely, Cat Swarm Optimization (CSO). CSO is generated by observing the
behaviors of cats, and composed of two sub-models, i.e., tracing mode and
seeking mode, which model upon th
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A combination of genetic algorithm and particle swarm optimization for optimal
DG location and sizing in distribution systems
Distributed generation (DG) sources are becoming more prominent in distribution systems due to the
incremental dema
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