Prediction Based on PSO-SVM in Power Communication Network Traffic

Zhen Dong Zhao; Rui Ju Xiao; Meng Meng Pei; Yi Zhou

doi:10.4028/www.scientific.net/AMM.602-605.2889

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Prediction Based on PSO-SVM in Power Communication Network Traffic

Abstract:

Power communication network traffic prediction is important basis of safely assigning and economically running. The forecasting precision will directly affect the reliability, economy running and supplying power quality of power system. Paper first expounds the electric power communication network traffic prediction research present situation, summarized the characteristics of the forecast and the influencing factors, summarizes the commonly used method, is put forward to the return of the electric power communication network traffic based on libsvm prediction method, and the PSO (particle swarm optimization) algorithm is adopted to model parameters optimization, with the test set error as the decision, based on the optimization of model parameters, choice, makes the prediction precision is improved.