北京邮电大学学报

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北京邮电大学学报

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基于熵权-灰色模型的电力数据网风险预测

李文璟1, 李梦1, 邢宁哲2, 纪雨彤2, 曾祥健1   

  1. 1. 北京邮电大学 网络与交换技术国家重点实验室, 北京 100876;
    2. 国网冀北电力有限公司 信息通信分公司, 北京 100053
  • 收稿日期:2017-06-30 出版日期:2018-06-28 发布日期:2018-06-28
  • 作者简介:李文璟(1973-),女,教授,博士生导师;李梦(1993-),女,硕士生,E-mail:lidameng@bupt.edu.cn.
  • 基金资助:
    国家电网科技项目(52010116000W)

Risk Prediction of Power Data Network Based on Entropy Weight-Gray Model

LI Wen-jing1, LI Meng1, XING Ning-zhe2, JI Yu-tong2, ZENG Xiang-jian1   

  1. 1. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China;
    2. State Grid Jibei Electric Power Company Limited Information & Communication Dispatch, Beijing 100053, China
  • Received:2017-06-30 Online:2018-06-28 Published:2018-06-28

摘要: 针对当前电力数据网风险预警模型无法有效预测网络风险的现状,提出一种基于熵权-灰色模型的电力数据网风险预测机制,重点解决网络整体风险的预测问题.首先利用灰色模型对电力数据网的风险指标进行预测,确定单项风险指标值;然后采用熵权法得出每一项指标的动态权重;最后根据风险指标值和权重得出网络整体的预测风险值.仿真验证结果表明,该模型可保证动态网络下实时预测的准确度.

关键词: 灰色预测, 熵权, 风险预警, 电力数据网

Abstract: Aiming at the present situation that risk prediction model of power data network cannot effectively predict the risk, a risk prediction mechanism of power data network based on entropy weight-gray model is proposed. This paper focuses on risk prediction of the entire network. Firstly, the gray model is used to predict the risk indexes of power data network, and the individual risk index value is determined. Then, the dynamic weight of each index is obtained by entropy weight method. Finally, it can calculate the risk value of the network according to the risk index value and the weight. The simulation results show that the proposed model can guarantee predictive accuracy of dynamic real-time network.

Key words: gray prediction, entropy method, risk warning, power data network

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