Title: Least Squares Support Vector Machine Parameter Optimization Algorithm
Abstract: To least squares support vector machine(LS-SVM) parameter optimization problems,proposed parameter self-adjustment optimization algorithm of LS-SVM of cross-validation and trained it with the data of non-linear test functions,and then utilized it for underwater FCAW penetration in multi-information on-line monitoring.Finally,compared LS-SVM with the prediction result of traditional BP network,the result showed that the model's prediction accuracy was satisfactory,the method in the paper was feasible.
Publication Year: 2010
Publication Date: 2010-01-01
Language: en
Type: article
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