Parameters Selection and Application of LS-SVM Based on Chaotic Ant Swarm Algorithm

Abstract:

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Parameters selection plays an important role for the performance of least squares support vector machines (LS-SVM). In this paper, a novel parameters selection method for LS-SVM is presented based on chaotic ant swarm (CAS) algorithm. Using this method, the optimization model is established, within which the fitness function is the mean square error (MSE) index, and the constraints are the ranges of the designing parameters. The proposed method is used in the identification for inverse model of the nonlinear systems, and simulation results are given to show the efficiency.

Info:

Periodical:

Advanced Materials Research (Volumes 204-210)

Edited by:

Helen Zhang, Gang Shen and David Jin

Pages:

423-426

DOI:

10.4028/www.scientific.net/AMR.204-210.423

Citation:

C. L. Xie et al., "Parameters Selection and Application of LS-SVM Based on Chaotic Ant Swarm Algorithm", Advanced Materials Research, Vols. 204-210, pp. 423-426, 2011

Online since:

February 2011

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Price:

$35.00

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