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灰色聚类分析在地质灾害综合区划中的应用
引用本文:于远祥,杨勇,叶万军.灰色聚类分析在地质灾害综合区划中的应用[J].煤田地质与勘探,2009,37(3):45-48.
作者姓名:于远祥  杨勇  叶万军
作者单位:1. 西安科技大学建筑与土木工程学院, 陕西 西安 710054;
摘    要:地质灾害作为一种主要的自然灾害,其综合区划研究成为当前学术界重要的前沿课题。利用灰色聚类分析的相关理论,在确立评价指标体系原则及要求的基础上,建立基于区域多源信息融合的地质灾害综合评价指标体系和评价模型,对陕西铜川地区的区域灾害程度进行了定量评价并得到地质灾害的聚类区划图谱。该地区可划分为极重灾、重灾和中灾3大片区,所得结果与区域实际灾情基本吻合。研究表明,灰色聚类分析的数学模型可以实现区域地质灾害的定量区划研究。

关 键 词:地质灾害  综合区划  灰色聚类分析  铜川地区
收稿时间:2008-11-11

Application of cluster aggregation analysis to the synthetic regionalization of the geological disasters
YU Yuanxiang,YANG Yong,YE Wanjun.Application of cluster aggregation analysis to the synthetic regionalization of the geological disasters[J].Coal Geology & Exploration,2009,37(3):45-48.
Authors:YU Yuanxiang  YANG Yong  YE Wanjun
Institution:1. College of Architecture and Civil Engineering, Xi'an University of Science and Technology, Xi'an 710054, China;2. College of Electrical and Control Engineering, Xi'an University of Science and Technology, Xi'an 710054, China;3. College of Geology and Environment, Xi'an University of Science and Technology, Xi'an 710054, China
Abstract:As a major kind of natural hazards, geological disasters have become the world problem. The synthetic regionalization of geological disasters has been put forward as an important subject for academic circles. According to the theory of fuzzy cluster aggregation analysis methods, this article discusses the comprehensive index, establishes a regionalization model of the geological disasters that is based on the amalgamation method with many data resources and analyzes the situation of the geological disasters in Tongchuan district quantitatively. Finally, the cluster atlas with three disaster areas, i.e, extremely serious disaster area, serious disaster area, middle disaster area were derived by the calculation method of fuzzy cluster aggregation. The results are almost consistent with the actual disasters.This paper shows the model of fuzzy cluster aggregation analysis can analyze the synthetic regionalization of the geological disasters quantitatively. 
Keywords:geological hazards  comprehensive regionalization  fuzzy cluster aggregation analysis  Tongchuan
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