中国电力 ›› 2014, Vol. 47 ›› Issue (7): 113-117.DOI: 10.11930/j.issn.1004-9649.2014.7.113.4

• 信息与通信 • 上一篇    下一篇

电网突发事件的网络舆情预警方法

朱朝阳1, 刘建明2, 王宇飞1   

  1. 1. 中国电力科学研究院 信息通信研究所,北京 100192;
    2. 国家电网公司,北京 100031
  • 收稿日期:2014-03-12 出版日期:2014-07-18 发布日期:2015-12-10
  • 作者简介:朱朝阳(1974—),男,江西新干人,博士,高级工程师,从事电力安全与应急管理技术研究。E-mail: zhucy@epri.sgcc.com.cn

A Novel Early-warning Method for the Network Public Opinion of Power Grid Emergency

ZHU Chao-yang1, LIU Jian-ming2, WANG Yu-fei1   

  1. 1. Information & Communication Department, China Electric Power Research Institute, Beijing 100192, China;
    2. State Grid Corporation of China, Beijing 100031, China
  • Received:2014-03-12 Online:2014-07-18 Published:2015-12-10

摘要: 为了实现电网突发事件网络舆情的精确预警,运用信息安全风险评估理论分析得出了导致电网突发事件网络舆情的各类影响因素,并设计了基于支持向量机的网络舆情预警指标体系。将预警指标体系的构造过程抽象为分类问题,将各类影响因素作为分类问题的输入量,预警等级作为分类问题的输出量,并利用支持向量机求解分类问题,有效地避免了传统方法中主观性较强的缺点。最后基于2012年4月10日深圳停电事件网络舆情监测数据的验证性实验,表明该方法在运算耗时和预警精度等方面的性能优异。

关键词: 电网突发事件, 网络舆情, 预警指标体系, 分类问题, 支持向量机

Abstract: In order to achieve accurate early-warning of network public opinion for electric power grid emergency, various kinds of influencing factors leading to the network public opinion of electric power grid emergency were gotten with the information security risk assessment theory, and a novel network public opinion early-warning index system was also proposed based on support vector machine. The designing process of early-warning system was abstracted into the classification problem by the way that the values of all indices were treated as the inputs of classification, and the early-warning levels were treated as the outputs of classification. Support vector machine was used to solve the classification problem, which can effectively avoid the subjective shortcomings of the traditional methods. Finally, the validation experiment based on the network monitoring data of the Shenzhen blackouts on April 10, 2012 shows that this support vector machine-based early-warning system has good performance in time consuming and alarm accuracy.

Key words: electric power grid emergency, network public opinion early-warning, network public opinion early-warning system, classification problem, support vector machine

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