Mixture kernel function of support vector machines

Kernel function is the key issue of Support Vector Machines (SVM), and different kernel functionscan produce different SVM. As the general kernel functions have their own advantages and disadvantages, to get a kernel function with stronger learning and generalization ability, a newmixture kernel function was proposed based on the fundamental of the kernel function, that the combination of the kernel functions still be a kernel function.The new kernel function had the desirable characteristics for SVM learning and generalization, and learned the advantages of global kernels and local kernels. The comparison results between the newkernel and other kernels in forecast of process supply chain experiment certify that the new kernel can achieve better performance than other kernels.