Network anomaly recognition based on cauchy particle swarm optimization algorithm-RBF neural network

Network anomaly recognition based on Cauchy particle swarm optimization algorithm-RBF Neural Network is presented in this paper. We collect 300 samples of KDDCUP99 datasets to study the network anomaly recognition ability based on Cauchy particle swarm optimization algorithm-RBF neural network. We employ the particle swarm optimization algorithm-RBF neural network model, traditional RBF neural network model to compare with the Cauchy particle swarm optimization algorithm-RBF neural network model. The network anomaly recognition results of the Cauchy particle swarm optimization algorithm-RBF neural network model shows that only 2 samples are incorrectly classified. The testing results show that the network anomaly recognition ability of Cauchy particle swarm optimization algorithm-RBF neural network is better than that of the particle swarm optimization algorithm-RBF neural network model, traditional RBF neural network model.