Algorithm Researching of RBF Neural Network Based on Improved PSO
2011 ◽
Vol 179-180
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pp. 233-238
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Keyword(s):
In view of the defect of particle swarm optimization which easily gets into partial extremum, the paper put out an improved particle swarm optimization, and applies the algorithm to the selecting of parameter of RBF neural network basal function. It searches the best parameter vector in the whole space, according to coding means, iterative formula, adapted function which the paper puts forwards. The experiment proves that RBF neural network based on improved PSO has faster convergent speed, and higher error precision.
2013 ◽
Vol 333-335
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pp. 1384-1387
Keyword(s):
2006 ◽
pp. 577-583
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