Abstract
Aiming at the accurate prediction of network security situation in power dispatching automation system, a network security situation awareness method based on LDA-RBF is proposed in this paper. In this method, the network security situation awareness is abstracted as a multi-dimensional numerical quantization problem, and a large number of field actual test samples are used as data sources to input the situation awareness model to characterize the perceived results. Based on the linear discriminant analysis (LDA), the test data is preprocessed to optimize the sample data, and the RBF neural network is used to find the nonlinear mapping relation of the network situation value, and the network security situation is quantified. Based on the linear discriminant analysis, the test data is preprocessed to optimize the sample data, and the RBF neural network is used to find the nonlinear mapping relation of the network situation value, so as to quantify the network security situation of the power dispatching automation system. Finally, the effectiveness of the proposed method in the security situation analysis of power dispatching automation system is verified through experiments in real network environment.
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