在加权模糊c -均值(FCM)聚类算法的基础上，对分色算法进行了改进。

An improved color segmentation algorithm is presented based on weighting fuzzy c-means (FCM) clustering algorithm.

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通过以全体样本对全体类别加权广义欧氏权距离平方和最小为目标函数，建立了模糊聚类、识别与优选决策统一的理论与循环迭代模型。

With the minimum square sum of weighted Euclidean distances as the objective function, the unified theory and cyclical iteration model of fuzzy cluster, recognition and optimum decision are founded.

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在模糊综合评判和灰色聚类评价法中，各个指标间总是采用单一的线性加权的方法。

In fuzzy synthetic evaluation and grey cluster evaluation, linear weighing method is commonly used for dealing with the relationship of each index.

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