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Title: Hybrid particle swarm optimization with wavelet mutation and its industrial applications
Authors: Ling, SH
Iu, HHC
Chan, KY
Lam, HK
Yeung, BCW
Leung, FHF 
Issue Date: Jun-2008
Source: IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics, June 2008, v. 38, no. 3, p. 743-763
Abstract: A new hybrid particle swarm optimization (PSO) that incorporates a wavelet-theory-based mutation operation is proposed. It applies the wavelet theory to enhance the PSO in exploring the solution space more effectively for a better solution. A suite of benchmark test functions and three industrial applications (solving the load flow problems, modeling the development of fluid dispensing for electronic packaging, and designing a neural-network-based controller) are employed to evaluate the performance and the applicability of the proposed method. Experimental results empirically show that the proposed method significantly outperforms the existing methods in terms of convergence speed, solution quality, and solution stability.
Keywords: Load flow problem
Modeling
Mutation operation
Neural network control
Particle swarm optimization
Wavelet theory
Publisher: Institute of Electrical and Electronics Engineers
Journal: IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics 
ISSN: 1083-4419
DOI: 10.1109/TSMCB.2008.921005
Rights: © 2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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