Research on Nonlinear Modeling Method of Support Vector Machine with Wavelet Derivation Kernel Function

Abstract

The model capability of Support Vector Machine (SVM) relies on the selection of kernel function. To obtain a better application modeling of SVM, the wavelet kernel function that satisfies Merce condition is introduced to use the kernel function of SVM, achieving a good effect. In the paper, on the basis of wavelet kernel function, a wavelet derivation kernel function is proposed in the application of SVM for higher accuracy. An actual example on nonlinear function approximation shows that SVM regression model has a satisfactory approximation effect, and also support an effective nonlinear modeling method.