Title: A Recursive Gradient Method of Least Square Support Vector Machine and its Application
Abstract: Least Square Support Vector Machine (LS-SVM) is an important machine of Support Vector Machine (SVM). But this method can not be used for online identification, and maybe lead to calculation inflation. A gradient recursive method of LS-SVM is presented by combining the LS-SVM method with the gradient method. This method can overcome the influence of bad data to the parameter estimation, has a stronger robustness, and improves the calculation speed of LS-SVM. The presented method is applied to the modeling of chaotic series. The simulation example validates the validity of the presented method.
Publication Year: 2013
Publication Date: 2013-07-01
Language: en
Type: article
Indexed In: ['crossref']
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