Abstract
In order to predict the operational risk of the power communication network more comprehensively and accurately, this paper presents a BP neural network model based on Levenberg-Marquardt (LM) algorithm. Firstly, establishing a set of indicators that reflect the operational characteristics of the power communication network. These indicator data are used as input to the model. Then, the operating efficiency of the traditional BP neural network is improved by the LM algorithm. The research results show that the model is simple, the forecast performance is stable and the accuracy is high, which provides an effective theoretical basis and modeling method for the prediction of power communication network risk.
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