计算机应用研究2016，Vol.33Issue(5)：1473-1476,1485,5.DOI:10.3969/j.issn.1001-3695.2016.05.044
正态分布的贝叶斯网络火灾数据融合预警研究
Research on early warning of fire data fusion of Bayesian network based on normal distribution
摘要
Abstract
In recent years,application of WSN tends to increasing node number,diversing module functions and complex applica-tion environment.Fusion data of fire monitoring and warning system are easy to be abnormal for node failure.In order to improve the precision of fire fusion data,this paper introduced the Gauss model.According to the entropy from fusing similar information between nodes,it ultilized the fusion outcome to express uncertainty.And it identified the fusion effect.The data fusion of Bayesian network based on the normal distribution was reasoning.In the simulation experiment,3 kinds of commonly used fire detection in-formation were fusion.The improved static and dynamic Bayesian networks were used to be analysis.Simulating fire scene with FDS,detection information discrete interval and incidence could be obtained by experiment.The conditional probability of the out-put nodes was calculated with BayesiaLab.Finally,the conclusion was obtained with Visual C++and the discretization step.It was the basis of selecting the threshold limit of detection information.And the early fire alarm response could be accurate fast reca-tion.关键词
正态分布/贝叶斯网络/火灾数据融合/预警Key words
normal distribution/Bayesian network/fire data fusion/early warning分类
信息技术与安全科学引用本文复制引用
金杉,崔文,金志刚..正态分布的贝叶斯网络火灾数据融合预警研究[J].计算机应用研究,2016,33(5):1473-1476,1485,5.基金项目
国家自然科学基金资助项目 （）
