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Extended Fuzzy C-Means Clustering in GIS Environment for Hot Spot Events

机译:GIS环境中热点事件的扩展模糊C均值聚类

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摘要

The Extended Fuzzy C-Means (EFCM) algorithm in a Geographic Information System (GIS) is used for identifying the volume clusters as Hot Spot areas, being the data events geo-referenced as points on the geographic map. We have implemented EFCM with the usage of the software tools ESRI/ARCGIS and ESRI/ARCVIEW 3.x and moreover we have made a comparison with the classical Fuzzy C-Means (FCM) algorithm. The application concerns a specific problem of maintenance, executed in the years 2001-2005, over the buildings constructed before 1960 in the city of Cava de' Tirreni, located in the district of Salerno (Italy).
机译:地理信息系统(GIS)中的扩展模糊C均值(EFCM)算法用于将卷聚类识别为热点区域,这是地理参考为地理地图上点的数据事件。我们已经使用软件工具ESRI / ARCGIS和ESRI / ARCVIEW 3.x来实现EFCM,并且与经典的模糊C均值(FCM)算法进行了比较。该申请涉及一个特定的维护问题,该问题在2001年至2005年间对位于萨莱诺(意大利)Cava de'Tirreni市的1960年之前建造的建筑物进行了维护。

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