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- W2365606331 abstract "In order to improve the classification effectiveness of Self-organizing feature Mapping(SOM) neural network,this paper designs a Supervised Self-organizing feature Mapping(SSOM) network,which adds output layer into the network structure based on input layer and competitive layer.According to different prediction category of input samples,SSOM selects different formula to adjust weights and train network.Through combinations of two weights,SSOM realizes the regression and statistic of the sample classes.Experiments on KDD CUP99 dataset show that SSOM has better classification ability and higher intrusion detection rate." @default.
- W2365606331 created "2016-06-24" @default.
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- W2365606331 date "2012-01-01" @default.
- W2365606331 modified "2023-09-22" @default.
- W2365606331 title "Application of Supervised SOM Neural Network in Intrusion Detection" @default.
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