A novel study of fuzzy clustering algorithms for their applications in various domains

Prashant Vats
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引用次数: 1

Abstract

Fuzzy clustering techniques allows for a meaningful generalizations to be made in bulk quantities of data by recognizing a few basic patterns among them. Fuzzy clustering approach is based on statistical analysis of data sets for determining whether the objects of a space would fall into different groups by making quantifiable comparisons of multiple characteristics. This technique finds its applications in providing solutions to a number of real time problems. So in this paper we have enlisted few applications of Fuzzy clustering technique into various areas for their useful results produced by the application of this technique into the respective areas.
对模糊聚类算法在各个领域的应用进行了新的研究
模糊聚类技术允许通过识别其中的一些基本模式,对大量数据进行有意义的归纳。模糊聚类方法是基于对数据集的统计分析,通过对多个特征进行可量化的比较,确定空间的对象是否属于不同的组。这种技术的应用是为许多实时问题提供解决方案。因此,本文列举了模糊聚类技术在各个领域的一些应用,并对该技术在各个领域的应用产生了有益的结果。
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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