In computer science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. It solves a problem by having a population of candidate solutions, here dubbed particles, and moving these particles around in the search-space according to simple mathematical formulae over the particle's position and velocity. Each particle's movement is influenced by its local best known position, but is also guided toward the best known positions in the search-space, which are updated as better positions are found by other particles. This is expected to move the swarm toward the best solutions.

Filename	Size	Update
chapter13粒子群优化算法的寻优算法
chapter13粒子群优化算法的寻优算法\.DS_Store	6148	2017-12-07
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chapter13粒子群优化算法的寻优算法\chapter13
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__MACOSX\._chapter13粒子群优化算法的寻优算法	172	2017-12-07

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