基于范例推理的灾害性地震应急物资需求预测研究
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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.
引文
[1]MA Chang-xi,QI Bo,DIAO Ai-xia.The application of improved ant colony algorithm for emergency logistics vehiclerouting problem[J].International Journal of Advancements in Computing Technology,2011,3(10):307-314.
    [2]MA Chang-xi,LI Yin-zhen,HE Rui-chun.Research on location problem of emergency service facilities based on genetic-simulated annealing algorithm[J].International Journal of Wireless and Mobile Computing,2012,5(2):206-211.
    [3]郭金芬,周刚.大型地震应急物资需求预测方法研究[J].价值工程,2011,30(22):27-29.GUO Jin-fen,ZHOU Gang.Research on emergency material demand forecast method under large-scale earthquakes[J].Value Engineering,2011,30(22):27-29.
    [4]傅志妍,陈坚.灾害应急物资需求预测模型研究[J].物流科技,2009,32(10):11-13.FU Zhi-yan,CHEN Jian.Research on emergency material demand forecast model in disaster[J].Logistics Science-Tech-nology,2009,32(10):11-13.
    [5]张晓磊,杨西龙,展丽潇.基于模糊相似推理的应急物资需求预测模型研究[J].物流技术,2012,31(5):229-231.ZHANG Xiao-lei,YANG Xi-long,ZHAN Li-xiao.Study on fuzzy similarity inference-based model for emergency materialdemand forecasting[J].Logistics Technology,2012,31(5):229-231.
    [6]陈安,陈宁,武艳南.现代应急管理技术与系统[M].北京:科学出版社,2011:100-110.CHEN An,CHEN Ning,WU Yan-nan.Modern Emergency Management Technology and System[M].Beijing:SciencePress,2011:100-110.
    [7]杨杰,朱思诚,刘茂.基于能力谱的地震建筑破坏造成人员伤亡评估[J].中国安全科学学报,2011,21(9):3-8.YANG Jie,ZHU Si-cheng,LIU Mao.Application of capacity spectrum for assessing earthquake casualties caused bybuildings damage[J].China Safety Science Journal,2011,21(9):3-8.
    [8]张洁,高惠瑛,刘琦.基于汶川地震的地震人员伤亡预测模型研究[J].中国安全科学学报,2011,21(3):59-64.ZHANG Jie,GAO Hui-ying,LIU Qi.Study on earthquake casualty forecasting model based on Wenchuanearthquake[J].China Safety Science Journal,2011,21(3):59-64.
    [9]韩小妹,韩景倜.基于CBR应急保障物流体智能决策支持系统研究[J].计算机工程与应用,2007,43(20):204-206.HAN Xiao-mei,HAN Jing-ti.Study of intelligent decision support system of ELS based on case-based reasoning[J].Computer Engineering and Applications,2007,43(20):204-206.
    [10]高俊杰,邓贵仕.基于本体的范例推理系统研究综述[J].计算机应用研究,2009,26(2):406-410.GAO Jun-jie,DENG Gui-shi.Survey on ontology-based CBR system[J].Application Research of Computers,2009,26(2):406-410.
    [11]张文修,吴伟志,梁吉玉.粗糙集理论与方法[M].北京:科学出版社,2003:2-10.ZHANG Wen-xiu,WU Wei-zhi,LIANG Ji-yu.Rough Set Theory and Methods[M].Beijing:Science Press,2003:2-10.
    [12]李寅煦.粗糙集在突发危机事件范例推理中的应用研究[J].陕西科技大学学报,2011,29(5):107-112.LI Yin-xu.Rough sets for CBR in emergency response[J].Journal of Shaanxi University of Science&Technology,2011,29(5):107-112.
    [13]沈惠璋.突发危机事件应急序贯群决策与支持系统[M].北京:科学出版社,2011.SHEN Hui-zhang.Sequential Group Decision Making and Group Decision Support Systems for Emergency Response[M].Beijing:Science Press,2011.
    [14]宁宣熙,刘思峰.管理预测与决策方法[M].北京:科学出版社,2009:290-291.NING Xuan-xi,LIU Si-feng.Management Forecast and Decision-making Methods[M].Beijing:Science Press,2009:290-291.
    [15]白建方.认识地震[M].北京:中国铁道出版社,2010:81-84.BAI Jian-fang.Know Earthquake[M].Beijing:China Railway Publishing House,2010:81-84.
    [16]克拉尼茶.4.14玉树地震[OL].[2012-04-20].http://baike.baidu.com/view/3481647.htm.Kelanicha.4.14 Yushu Earthquake[OL].[2012-04-20].http://baike.baidu.com/view/3481647.htm.

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