Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/23283
Title: Cauchy mutation based on objective variable of Gaussian particle swarm optimization for parameters selection of SVM
Authors: Wu, Q
Law, R 
Keywords: Particle swarm optimization
Gaussian mutation
Cauchy mutation
Support vector machine
Issue Date: 2011
Publisher: Pergamon Press
Source: Expert systems with applications, 2011, v. 38, no. 6, p. 6405-6411 How to cite?
Journal: Expert systems with applications 
Abstract: On the basis of the slow convergence of particle swarm algorithm (PSO) during parameters selection of support vector machine (SVM), this paper proposes a hybrid mutation strategy that integrates Gaussian mutation operator and Cauchy mutation operator for PSO. The combinatorial mutation based on the fitness function value and the iterative variable is also applied to inertia weight. The results of application in parameter selection of support vector machine show the proposed PSO with hybrid mutation strategy based on Gaussian mutation and Cauchy mutation is feasible and effective, and the comparison between the method proposed in this paper and other ones is also given, which proves this method is better than sole Gaussian mutation and standard PSO.
URI: http://hdl.handle.net/10397/23283
ISSN: 0957-4174
EISSN: 1873-6793
DOI: 10.1016/j.eswa.2010.08.069
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