A dissipative particle swarm optimization isdeveloped according to the self-organization of dissipativestructure. The negative entropy is introduced to construct anopening dissipative system that is far-from-equilibrium so as todriving the irreversible evolution process with better fitness.The testing of two multimodal functions indicates it improvesthe performance effectively.structure. The negative entropy is introduced to construct anopening dissipative system that is far-from-equilibrium so as todriving the irreversible evolution process with better fitness.The testing of two multimodal functions indicates it improvesthe performance effectively.

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Particle Swarm Optimization Methods for Pattern Recognition and Image Processing
Particle Swarm Optimization Methods for Pattern Recognition and Image Processing\00front.pdf
Particle Swarm Optimization Methods for Pattern Recognition and Image Processing\01chapter1.pdf
Particle Swarm Optimization Methods for Pattern Recognition and Image Processing\03chapter3.pdf
Particle Swarm Optimization Methods for Pattern Recognition and Image Processing\04chapter4.pdf
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Particle Swarm Optimization Methods for Pattern Recognition and Image Processing\06chapter6.pdf
Particle Swarm Optimization Methods for Pattern Recognition and Image Processing\07chapter7.pdf
Particle Swarm Optimization Methods for Pattern Recognition and Image Processing\08chapter8.pdf
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