Prediction of network security situation awareness based on an improved model combined with neural network

People always pay attention to the security of network. This paper mainly analyzed problem network situation prediction (NSSP). The radial basis function neural was improved by particle swarm optimization algorithm, and a modified optimization-radial algorithm obtained, which used as model. Then, data from National Internet Emergency Center were experimental data, compared with algorithms. results showed that could achieve convergence in about 50 times iterations, showing high calculation efficiency short operation time, mean absolute percentage error value, square root-mean-square value small (2.13%, 0.0005, 0.0224), had good performance. verify reliability NSSP, is conducive further improve security.