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模糊均值聚类FCM算法对图像的颜色聚类 进行图像分割 聚类个数和聚类中心都是事先决定的-Fuzzy-means clustering algorithm FCM clustering for color image segmentation and clustering the number of cluster centers are determined in advance
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模糊C均值聚类（FCM），即众所周知的模糊ISODATA，是用隶属度确定每个数据点属于某个聚类的程度的一种聚类算法。-Fuzzy C means clustering (FCM), known as fuzzy ISODATA, is used to determine membership of each data point belongs to a cluster of a clustering algorithm level.
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fuzzy cluster means nice algorithm -fuzzy cluster means nice algorithm !!
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用类Cluster实现一维数据的模糊C均值聚类，可在VC＋＋和BC++下使用-Class Cluster fuzzy C-means clustering, one-dimensional data can be used in VC++ and BC++
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模糊C-均值算法容易收敛于局部极小点，为了克服该缺点，将遗传算法应用于模糊C-均值算法(FCM)的优化计算中，由遗传算法得到初始聚类中心，再使用标准的模糊C-均值聚类算法得到最终的分类结果。-Fuzzy C- means algorithm is easy to converge to a local minimum point, in order to overcome this drawback, the genetic algorithm is applied to fuzzy C- me
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Fuzzy clustering algorithms like the popular fuzzy c-means algorithm (FCM) are
frequently used to automatically divide up the data space into fuzzy granules. When the fuzzy clusters are used to derive membership functions for a fuzzy rule-based syst
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FCM算法是一种基于划分的聚类算法，它的思想就是使得被划分到同一簇的对象之间相似度最大，而不同簇之间的相似度最小。模糊C均值算法是普通C均值算法的改进，普通C均值算法对于数据的划分是硬性的，而FCM则是一种柔性的模糊划分。在介绍FCM具体算法之前我们先介绍一些模糊集合的基本知识。(The FCM algorithm is a partition-based clustering algorithm. Its idea is to make the similarity among the obj
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