Risk Early-Warning Model Based on SVM Decision Tree
CSTR:
Author:
Affiliation:

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    The security monitoring data of Dangerous chemicals business has great social value, especially real-time accurate prediction of the security risk has become a hot warning research. From the view of four dimensions which are people, equipment, the environment and management, this article analyzes the relevant indicators of safety hazards warning, constructs the bottom-up decision tree based on multi-classification SVM warning model, constructs a bottom-up decision tree SVM multi-classification model based on early warning, to achieve the security level of accurate classification and for future production safety status warning. By comparison with more top-down classification model, it confirms that early warning model used in this paper has better performance in real-time and accuracy, and meets the basic requirements of early warning models.

    Reference
    Related
    Cited by
Get Citation

闫晓静,于放,孙咏,肖卡飞,王嵩.支持向量机决策树在隐患预警模型中的应用.计算机系统应用,2017,26(2):212-216

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:May 16,2016
  • Revised:June 16,2016
  • Adopted:
  • Online: February 15,2017
  • Published:
Article QR Code
You are the firstVisitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-3
Address:4# South Fourth Street, Zhongguancun,Haidian, Beijing,Postal Code:100190
Phone:010-62661041 Fax: Email:csa (a) iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063