In the study, RBF neural network optimized by particle swarm optimization algorithm is applied to evaluate network safety. In the RBF neural network, the choice of the three parameters including the center of RBF, the width of RBF and the weight have an important influence on the classification performance of RBF neural network. Particle swarm optimization algorithm is used to select the optimal combination of the parameters of the RBF neural network parameters. The experimental results show that the network evaluation model based on PSO-RBF neural network has better evaluation performance than RBF neural network.
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