基于主成分分析方法的聚类分析方法在灾情综合分类中的应用

英文篇名：Principal Component Method Based on Cluster Analysis Applying on Classification of Earthquake Disaster
中文刊名：佳木斯大学学报(自然科学版)
英文刊名：Journal of Jiamusi University(Natural Science Edition)
作者：张永利 ; 傅俊伟
英文作者：ZHANG Yong-li1 ; FU Jun-wei2(1.College of Science ; Heilongjiang Institute of Science and Technology ; Harbin 150027 ; China ; 2.College of Science ; Qiqihar University ; Qiqihar 161006 ; China)
中文关键词：聚类分析 ; 主成分分析 ; 面积加权平均烈度 ; 地质灾害危险度 ; 转移安置率
英文关键词：cluster analysis ; principal component analysis ; area weighted average intensity ; earthquake disaster risk ; relocated rate
出版日期：2011-03-15
机构：黑龙江科技学院理学院;齐齐哈尔大学理学院;
年：2011
期：02
出版单位：佳木斯大学学报(自然科学版)

摘要

通过主成分分析方法选取地震的主要灾情指标,运用SPSS软件中的聚类分析方法,对汶川地震时,四川省各受灾地区按系统聚类法进行聚类分析,得出地区灾情综合分类.所得结果与原文给出结果基本一致,进而验证了基于主成分分析的聚类分析方法在灾情综合分类中应用的合理性.并且,提供了一种正确进行灾情评价和物资分配的有效方法.
In this paper,key indicators of earthquake disaster were selected by principal component analysis.By means of clustering analysis method of SPSS software,the disaster areas were classified according to the affected area of Wenchuan earthquake in Sichuan Province.And the area disaster classification was given.The results were consistent with the original results.And it is proved that the principal component method based on the cluster analysis applies on the disaster area classification is reasonable.The disaster classification provides an effective way of disaster assessment and proper distribution of supplies.

引文

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