Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10322318 | Expert Systems with Applications | 2012 | 16 Pages |
Abstract
⺠Feedback controlled particle swarm optimization can solve optimization problems effectively. ⺠A new particle evolutionary fitness function can control PSO parameters automatically. ⺠A new local learning method using a competitive penalized method can refine the solution. ⺠Feedback controlled PSO can be applied to a radial basis neural network for time-series prediction.
Related Topics
Physical Sciences and Engineering
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Authors
W.K. Wong, S.Y.S. Leung, Z.X. Guo,