摘要
基于范例推理(CBR)理论,利用最近相邻法和粗糙集理论搜索相似度最高的主震历史范例,分析各主要物资需求量的影响因素,预测当前范例主震期应急物资需求量。通过序贯决策,采用马尔科夫预测模型预测余震类型,进而搜索余震历史范例,预测余震期应急物资需求量。以"玉树"地震为例,运用该方法估算地震发生后食物类、生活用品类、药品类、工程机械类的需求量。
For a presumed present disastrous earthquake, the emergency material demand was predicted as mentioned below:highest similarity historical examples of it were searched out using Nearest Neighbor Algorithm and Rough Set knowledge based on the CBR theory; affecting factors on the demand were analyzed ; the main demand of emergency material after a principal seismic stage was predicted ; the aftershock type was predicted by sequential decision-making and adopting Markov forecast model, aftershock examples were searched out and the emergency material demand of aftershock was predicted. Taking Yushu earthquake as an example, the method was used to predict the demands of foods, living goods, drags and mechanical engineering things after earthquake.
出处
《中国安全科学学报》
CAS
CSCD
北大核心
2012年第8期3-9,共7页
China Safety Science Journal
基金
教育部人文社会科学研究项目(11YJA2H132
11YJC2H170
11XJC630009)
关键词
灾害性地震
应急物资需求
范例推理(CBR)
粗糙集
序贯决策
马尔科夫预测
disastrous earthquake
emergency material demand
case-based reasoning(CBR)
rough set
sequential decision-making
Markov forecast