Nonlinear Classifier Design Research Based on SVM and Genetic Algorithm

Abstract

This paper presents a support vector machine (SVM) model structure, the genetic algorithm parameters of the model portfolio optimization model, and used for non-linear pattern recognition, the method is not only effective for linear problems, nonlinear problems apply effective; the law simple and easy, better than the multi-segment linear classifier design methods and BP network algorithm returns the error. Examples show the efficiency of its recognition of 100%. DOI:  http://dx.doi.org/10.11591/telkomnika.v13i1.6692