A method for Network Security Situation Prediction Based on CMA一RBF Model

A method for Network Security Situation Prediction Based on CMA一RBF Model

A method for network security situation prediction is proposed，where the covariance matrix adaptation evolution strategy algorithm(CMA-ES)is used to optimize the parameters of the radial basis neural network forecasting model(RBF)，which makes the forecasting model have superior ability, and C月n func...

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Bibliographic Details
Main Authors: YANG Ming, HU Guan-yu, LIU Qian
Format: Article
Language:zho
Published: Harbin University of Science and Technology Publications 2017-04-01
Series:Journal of Harbin University of Science and Technology
Subjects:
network security situatron prediction; covariance】】atrix adaptation evolution strategy algorithm; Radial basis function neural network; time Ser1eS prediction
Description
Summary:A method for network security situation prediction is proposed，where the covariance matrix adaptation evolution strategy algorithm(CMA-ES)is used to optimize the parameters of the radial basis neural network forecasting model(RBF)，which makes the forecasting model have superior ability, and C月n function quickly find out the rules of the complex time pre(11Ct the netWOrk seCUrlty sltuatlOn， Ser1eS. The simulations results show that the proposed method tradltlOnal pre(11CtlOn can accurately and has better prediction accuracy than methods.
ISSN:1007-2683

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