A method for Network Security Situation Prediction Based on CMA一RBF Model
YANG Ming, HU Guan-yu, LIU Qian
Journal of Harbin University of Science and Technology · 2017
doi:10.15938/j.jhust.2017.02.026 (opens in a new tab)
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Abstract
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.
Abstract licence: CC BY
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