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论文类型：期刊论文

发表时间：2011-01-01

发表刊物：Journal of Computers

收录刊物：EI、Scopus

卷号：6

期号：9

页面范围：1935-1941

ISSN号：1796203X

摘要：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.