基于贝叶斯分类器的重大危险源辨识  

Identification of Major Hazards Based on Bayesian Classifier

作　　者：董立岩[1] 李真[1] 阎鹏飞[1] 

机构地区：[1]吉林大学计算机科学与技术学院,长春130012

出　　处：《吉林大学学报（理学版）》2009年第4期800-804,共5页Journal of Jilin University:Science Edition

基　　金：国家自然科学基金(批准号:60275026)

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.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 construc- ted 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.

关 键 词：贝叶斯分类器 数据挖掘 重大危险源辨识 应急预案 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]