Particle swarm optimization (PSO) is an evolutionary computing (evolutionary computation), there is invented by Dr. Eberhart and Dr. kennedy. From the behavior of birds of prey. PSO with genetic algorithm is similar to an iteration-based optimization tool. System is initialized to a group of random solutions, the optimal value by iterative search. But there is no genetic algorithm with the cross (crossover) and mutation (mutation). But the particles in the solution space to follow the optimal particle search. Comparison with genetic algorithms, PSO has the advantage of simple and easy to implement and there is no need to adjust many parameters. Has been widely used in function optimization, neural network training, fuzzy system control, and other genetic algorithm applications.

Particle algorithm.doc

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