Situation prediction based on variational objective fuzzy identification
WANG Na
ZHANG Xin-hai
CHANG Ya-ming
Abstract：In view of the strong non-stationarity and randomness existing in the network security situation data,to improve the accuracy of network security situation prediction,a method via variational objective fuzzy identification is proposed.Firstly,the variational mode decomposition method is introduced and combined with the dynamic time warping method.Thus the original situation data set is decomposed and reconstructed.As a result,the stability of the proposed data set is increased and the number of decomposed modes is reduced.Simultaneously,the error and training cost of the subsequent model predictions is decreased;Secondly,the partial autocorrelation analysis method is used to determine the input variables of the T-S model.Followingly,the inputs are afforded to the algorithms of objective cluster analysis and the fuzzy c-means.Therefore the compact and accurate structure of the T-S model is obtained.As a result,the accuracy of the constructed T-S model is guaranteed.Finally,the validity of the presented method was tested using the NSL-KDD benchmark dataset of network intrusion detection simulation.
Keywords：situation predictionT-S modelfuzzy identificationvariational mode decompositiondynamic time warp-ingfuzzy clustering
Publication Date：2025-09-30
Online Publishing Date：2025-10-28(First online date of this platform, not the publication date of the document)
Pages：9( 1789-1797 )