In this paper we present a method

GA-MKL

by using the genetic algorithm to optimize the weights of linear multi-kernel support vector machine.We first implement single-kernel experiment to decide the best parameter of each kernel then construct the linear multi-kernel with these indeterminate weights.Then we utilize the genetic algorithm to find the best weights which give the best classification performance.The classification experiments on the UCI database are employed with this algorithm.By comparison with the single-kernel algorithm

the experimental results show that this algorithm is superior to the single-kernel

thus it provides a feasible method for finding the best weights for multi-kernel SVM.This algorithm performs better than other MKL algorithm as well.