Release Time:2019-03-11  Hits:

Indexed by: Journal Article

Date of Publication: 2011-01-01

Journal: Journal of Computers

Included Journals: Scopus、EI

Volume: 6

Issue: 9

Page Number: 1935-1941

ISSN: 1796203X

Abstract: Parameters optimization plays an important role for the performance of least squares support vector machines (LS-SVM). In this paper, a novel parameters optimization 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. After having been validated its effectiveness by an artificial data experiment, the proposed method is then used in the identification for inverse model of the nonlinear underactuated systems. Finally real data simulation results are given to show the efficiency. ? 2011 ACADEMY PUBLISHER.