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A fault identification with fuzzy C-Mean clustering
algorithm based on improved ant colony algorithm (ACA) is
presented to avoid local optimization in iterative process of
fuzzy C-Mean (FCM) clustering algorithm and the difficulty in
fault cl
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模糊C均值脑电分类并使用了支持向量机对比，其中支持向量机使用了三种方法参数寻优。-fuzzy C means clustering for EEG classification，and use the SVM for campare. The SVM applied three methods to find the optimal apartments.
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提出一种基于模糊C 均值的支持向量机分类算法，通过模糊C 均值算法对未知类别数据
进行划分，然后再利用支持向量行对划分后的数据机进训练。解决了以往人们应用支持向量机进行
数据分类识别前必须采用已知类别的数据对支持向量机进行训练的弊端，提高了数据分类的效率。-Support vector machines classification algorithm is proposed based on Fuzzy C-Means, Fuzzy C-Means algorithm unknown
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Segmentation of M-FISH Images for Improved Classification of Chromosomes with an Adaptive Fuzzy C-means Clustering Algorithm
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Suitable sampling technique in
contextual fuzzy c-means classification
of remotely sensed data for land cover
mapping
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