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A Combined System for Regionalization in Spatial Data Mining Based on Fuzzy C-Means Algorithm with Gravitational Search Algorithm

机译:基于模糊C型算法的空间数据挖掘区域化组合系统,引力搜索算法

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The proposed new hybrid approach for data clustering is achieved by initially exploiting spatial fuzzy c-means for clustering the vertex into homogeneous regions. Further to improve the fuzzy c-means with its achievement in segmentation, we make use of gravitational search algorithm which is inspired by Newton's rule of gravity. In this paper, a modified modularity measure to optimize the cluster is presented. The technique is evaluated under standard metrics of accuracy, sensitivity, specificity, Map, RMSE and MAD. From the results, we can infer that the proposed technique has obtained good results.
机译:通过最初利用用于将顶点聚类为均匀区域的空间模糊C-inse来实现数据聚类的所提出的新混合方法。 进一步提高模糊C-inse以分割的成就,我们利用了引力搜索算法,该算法由牛顿的重力调测。 在本文中,介绍了优化群集的修改模块化度量。 该技术在准确度,敏感度,特异性,地图,RMSE和MAD的标准度量下评估。 从结果中,我们可以推断提出的技术获得了良好的效果。

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