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首页> 外文会议>International Conference on Inventive Computation Technologies >Fuzzy C-means algorithm with gravitational search algorithm in spatial data mining
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Fuzzy C-means algorithm with gravitational search algorithm in spatial data mining

机译：空间数据挖掘中具有引力搜索算法的模糊C均值算法

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There has been unprecedented growth of spatial data encountered in different application domains and their analysis has become more important and practically relevant. Clustering is one of the important tasks in spatial data mining and its issues have been extensively studied. In this paper, we propose a new hybrid approach for data clustering. Initially the proposed approach exploits spatial fuzzy c-means for clustering the vertex into homogeneous regions. In order to improve the performance of fuzzy c-means to cope with segmentation problems, we employ gravitational search algorithm which is inspired by Newton's rule of gravity. Gravitational search algorithm is incorporated into fuzzy c-means to take advantage of its ability to find optimum cluster centers which minimizes the fitness function of fuzzy c-means.
机译：在不同的应用领域中遇到的空间数据有了空前的增长，它们的分析变得越来越重要，并且在实践中也越来越重要。聚类是空间数据挖掘中的重要任务之一，其问题已得到广泛研究。在本文中，我们提出了一种新的数据聚类混合方法。最初，所提出的方法利用空间模糊c均值将顶点聚类为均匀区域。为了提高模糊c均值处理分割问题的性能，我们采用了受牛顿引力定律启发的引力搜索算法。引力搜索算法被结合到模糊c均值中，以利用其找到最佳聚类中心的能力，从而使模糊c均值的适应度函数最小。

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