首页> 外文会议>2016 12th International Conference on Mathematics, Statistics, and Their Applications >Spatial clustering for determining rescue shelter of flood disaster in South Bandung using CLARANS Algorithm with Polygon Dissimilarity Function
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Spatial clustering for determining rescue shelter of flood disaster in South Bandung using CLARANS Algorithm with Polygon Dissimilarity Function

机译:基于多边形异函数的CLARANS算法确定南万隆南部洪水灾害救援避难所的空间聚类。

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In this research, we provide a solution to the problem of handling the recent flooding in South Bandung, West Java, Indonesia. We offer the solution in determining the locations of the rescue posts. The analysis uses a spatial data clustering algorithm known as CLARANS Algorithm and the spatial similarity is measured using Polygon Dissimilarity Function (PDF). Results showed that clustering of two clusters gives the strongest Silhouette index value of 0.9, and clustering of 4 and 5 clusters have a Silhouette index value of 0.8. Clustering process is done quickly, less than 3 seconds for 2 clusters and less than 4 seconds for 5 clusters.
机译:在这项研究中,我们为解决印度尼西亚西爪哇省南万隆市最近的洪水问题提供了解决方案。我们提供确定救援站位置的解决方案。该分析使用称为CLARANS算法的空间数据聚类算法,并使用多边形不相似函数(PDF)测量空间相似性。结果表明,两个聚类的聚类给出的最强Silhouette指数值为0.9,4个聚类和5个聚类的聚类给出的Silhouette指数值为0.8。群集过程很快完成,对于2个群集,少于3秒,对于5个群集,少于4秒。

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