J4 ›› 2009, Vol. 47 ›› Issue (4): 795-799.

• 计算机科学 • 上一篇    下一篇

基于贝叶斯分类器的重大危险源辨识

董立岩, 李真, 阎鹏飞   

  1. 吉林大学 计算机科学与技术学院, 长春 130012
  • 收稿日期:2009-03-10 出版日期:2009-07-26 发布日期:2009-08-24
  • 通讯作者: 董立岩 E-mail:dongly@jlu.edu.cn.

Identification of Major Hazards Based on Bayesian Classifier

 DONG Li-Yan, LI Zhen, YAN Feng-Fei   

  1. College of Computer Science and Technology, Jilin University, Changchun 130012, China
  • Received:2009-03-10 Online:2009-07-26 Published:2009-08-24
  • Contact: DONG Li-Yan E-mail:dongly@jlu.edu.cn.

摘要:

针对应急领域重大危险源的识别问题, 提出一种新的识别模型: 基于贝叶斯分类器的重大危险源识别模型. 先利用已知知识建立模型, 再根据建立的模型运用概率判断新的识别对象是否为重大危险源. 分别将识别模型应用于化工产品生成领域和森林防火领域, 实验结果与实际情况相符, 表明该模型效果较好.

关键词: 贝叶斯分类器, 数据挖掘, 重大危险源辨识, 应急预案

Abstract:

In view of the problem of major hazards identification in emergency response domain, we proposed a new identification model, Bayesian based major hazards identification model. First the model was constructed with the aid of known knowledge, then major hazards were identified according to the constructed model via probability. We applied this model to chemical production area and forest fire prevention area respectively, obtaining the results reasonable. Practice shows this way is effective.

Key words: Bayesian classifier, data mining, major hazards identification, emergency response plan

中图分类号: 

  • TP399