FCM Algorithm: Analysis of the Membership Function Influence and Its consequences for fuzzy clustering

Luis Mantilla, Yessenia Yari
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引用次数: 1

Abstract

Image segmentation in satellite images is a task widely investigated since we can extract some information of an image and analyze it. We propose to use a weighted factor for each of the distances used to calculate the degree of membership of each element to the cluster. In this way, we seek to reduce the influence of the upper and the lower bounds on the FCM equa. tion. This paper reports preliminary results of the experiments and shows that the proposed algorithm performs accurately on a real dataset. For the evaluation of the algorithm, different cluster validity indexes are employed.
FCM算法:隶属函数对模糊聚类的影响及其后果分析
卫星图像的图像分割是一个被广泛研究的问题,因为我们可以提取图像的某些信息并对其进行分析。我们建议对用于计算每个元素对集群的隶属度的每个距离使用加权因子。通过这种方式,我们寻求减少上限和下限对FCM方程的影响。。本文报告了初步的实验结果,并证明了该算法在真实数据集上的准确性。为了对算法进行评价,采用了不同的聚类有效性指标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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