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- W2363025458 abstract "In order to detect the network intrusion effectively,an artificial fish swarm( AFSA) algorithm is proposed to optimize the BP neural network( BPNN) intrusion detection model. In this paper,firstly,weights and threshold coding state of BP neural network is artificial fish of the AFSA,followed by artificial fish swarm foraging,Poly Group,rear end,which is used to optimize the parameters of BP neural network,to find the optimal parameters of the BP neural network; After that,using the establishment of optimal BP neural network model,the behavior of the network intrusion are detected. In the Windows XP operating system,on the platform of MATLAB 2012 by the KDD cup 99 data set of simulation test,compared with the traditional BP neural network model,the proposed model can significantly improve the network intrusion detection accuracy and has a more extensive application prospects." @default.
- W2363025458 created "2016-06-24" @default.
- W2363025458 creator A5004432550 @default.
- W2363025458 date "2015-01-01" @default.
- W2363025458 modified "2023-09-23" @default.
- W2363025458 title "Application of Back Propagation Neural Network Optimizing by Artificial Fish Swarm Algorithm in Network Intrusion Detection" @default.
- W2363025458 hasPublicationYear "2015" @default.
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