Application Of Network Security Forecast Based On Improved Grey Model For Electric Power Industry

The paper suggests a new forecasting model for the network security-related problems in the power industry to remedy the shortcomings of the traditional ones which fail to reflect the industry’s overall conditions and cannot predict with accuracy. The sample data are collected by analyzing the events concerning the network security of the power companies. Then AHP (Analytic Hierarchy Process) is applied to set up an indicator system to evaluate those data and form a sequential distribution of exceptional values. Based upon that, GM (Grey Model) is introduced to comprehensively predict the conditions of the industry’s information security, and then the prediction results are modified by using artificial neural network method. The simulating tests have also been carried out to prove that the proposed model with improved GM as the basis is viable and valid.In this paper, the main results were as follows:firstly it collects regular, analyzes and trims the data related to the network security of power companies, from which some variables containing more information are picked out to form an evaluation system;Secondly, To deal with the filtered information, using the method of AHP (Analytic Hierarchy Process) in order to get the index weight, and then construct the evaluation system of network security;Thirdly,it reviews the status-quo and then forms a comparison between neural network and gray model, based on which a suitable and pragmatic prediction model is brought up that properly-processed data are input into and predicts the time sequence by the use of the gray model for forecasting catastrophic accidents. Then the model modifies the results by introducing them into the neural network model to get a desired predicted value reflecting the actual conditions of the network safety.