Prediction on internet safety situation of relevance vector machine about GP-RVM kernel function

Abstract

In prediction of network security situation, the prediction accuracy of traditional single kernel function vector machine is a little low. It can’t describe the randomness and abruptness, and it has some limitation. A network security forecasting model was put forward which combined Gaussian kernel function and polynomial kernel to solve this problem. Proved by simulation experiment, this model can increase prediction accuracy and it has some practical meaning.