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基于PCA的聚类分析在汶川地震灾情分类中的应用
Application of Cluster Analysis Based on Principal Component Analysis to Classification of Disaster in Wenchuan Earthquake
【摘要】 利用主成分分析(PCA)运用SPSS软件对汶川地震36个严重受灾县市的8个灾情指标进行了综合分析,得到了累积贡献率为83.403%的3个主成分及其得分;然后,基于3个主成分的得分采用聚类分析对汶川地震36个严重受灾县市进行了分类;得到了全面、合理和科学的分类结果。
【Abstract】 The comprehensive analysis is conducted on 8 disaster indicators of 36 seriously disaster-stricken counties and cities in Wenchuan Earthquake by principal component analysis and by SPSS software,three principal components and scores of cumulative contribution rate of 83.403% are obtained.Then,the classification for 36 seriously disaster-stricken counties and cities in Wenchuan Earthquake is conducted by cluster analysis based on the scores of three principal components.The comprehensive,rational and scientific classification results are obtained.
【关键词】 汶川地震;
灾情分类;
主成分分析;
聚类分析;
SPSS软件;
【Key words】 Wenchuan Earthquake; classification of disaster; Principal Component Analysis; Cluster Analysis; SPSS software;
【Key words】 Wenchuan Earthquake; classification of disaster; Principal Component Analysis; Cluster Analysis; SPSS software;
【基金】 云南省教育厅科学研究基金项目(2010C140)
- 【文献出处】 重庆工商大学学报(自然科学版) ,Journal of Chongqing Technology and Business University(Natural Science Edition) , 编辑部邮箱 ,2013年05期
- 【分类号】X43;P315.9
- 【下载频次】70