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psopt20130502b

于 2013-05-04 发布 文件大小:33KB
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  Particle swarm optimization is a derivative-free global optimum search algorithm based on the collective intelligence of a large group of intercommunicating entities. The individual particles are simple and primitive, knowing only their own current locations and fitness values, their personal best locations, and the swarm s best location. Each particle continually adjusts its trajectory based this information, moving towards the global optimum with each iteration. The swarm as a whole displays a remarkable level of coherence and coordination despite the simplicity of its individual particles. The coordinated behavior of the swarm has been compared with that of a flock of birds or a school of fish.

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