Intelligent substation network security situation prediction model based on Gibbs-LDA

Abstract

With the further smart grid, the research and application of network security situation awareness (NSSA) in smart substations are receiving more attention. In this paper, we propose a method of network safety forecasting for smart substations based on Gibbs-LDA and least square support vector machines. The project extracts all kinds of message information of intelligent substation network as message set, obtains sample characteristics and message set model, and establishes multi-dimensional prediction model of intelligent substation network security based on LDA. And use the least square support vector algorithm to get the prediction result. The experiment on the data set collected by smart substation shows that the method in this paper has the advantages of high prediction accuracy and short prediction time compared with other methods.