摘要
灾害、衍生和次生灾害及其相互耦合使得灾情恶化,作为灾害对抗力量的抢险、避险、控制的救险等措施使得灾害向灾情减轻的方向转化,本文对灾害的这一动态演化过程进行描述,建立一种综合考虑灾害的自然演化与抢险救灾行动的基于Bayes推理的灾害演化GERT(Graph Evaluation and Review Technique)网络模型;把GERT网络方法和贝叶斯推理工具相结合,根据获得的新信息,对GERT网络中活动参数进行动态修正,对灾害的演化路径,各种主要状态的演化概率和时间进行动态预测、预警与评价;对衍生与次生灾害、抢险救灾行动等外界行为对系统演化的影响进行定性与定量分析,并给出定量评价结论。本文提供了灾害演化定性与定量结合的分析框架与工具,揭示灾害演化机理,为灾害发展态势的预测、预警与评价提供了一种新的研究方法和研究思路。
The interaction between disasters,derived disasters and secondary disasters may make the disaster situation worse and hard to control.Rush emergency,risk avoiding and controlling for the process of disaster rescue,as countermeasures to the disaster,should play their role in turning the damage caused by the disaster as low as possible.The paper focuses on describing the dynamic evolutionary process,before establishing a GERT（Graph Evaluation and Review Technique） network model,taking the natural evolution of disaster and the action of emergency rescue into consideration,based on the Bayes reasoning.After that,by means of combining of GERT network methods and Bayes reasoning tools,according to the received new information,the paper makes dynamic modification to active parameters in GERT network,and measures like dynamic prediction,early-warning and evaluation have been taken against different probabilities and time of revolution in different situation.In the end,the paper gives qualitative and quantitative analysis to the influence to systematic revolution caused by external actions,like derived disaster and secondary disasters.In a word,this paper provides the framework and tools for the disaster evolution in the way of qualitative and quantitative analysis,which reveals the mechanism of disaster evolution,at the same time,it offers a new method and idea for the forecasting,early warning and evaluation of the disaster evolutionary tendency.
出处
《中国管理科学》
CSSCI
北大核心
2009年第2期102-107,共6页
Chinese Journal of Management Science
基金
国家自然科学基金项目(70473037,70701017)
江苏省高等学校首批优秀科技创新团队基金
南京航空航天大学创新集体和科研创新基金项目(Y0488-091)
教育部哲学社会科学研究后期资助项目(07JHQ0053)
江苏省哲学社会科学基金项目资助项目(07EYA017)
