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Application of Hard C-means and Fuzzy C-means in data fusion

机译:硬C型均值和模糊C型方法在数据融合中的应用

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This article describes two kinds of Fuzzy clustering algorithm based on partition,Fuzzy C-means algorithm is on the basis of the hard C-means algorithm, and get a big improvement, making large data similarity as far as possible together. As a result of Simulation, FCM algorithm has more reasonable than HCM method on convergence, data fusion, and so on.
机译:本文介绍了基于分区的两种模糊聚类算法,模糊C均值算法基于硬C均值算法,并获得了大的改进,尽可能大的数据相似性。 由于仿真结果,FCM算法比收敛,数据融合等的HCM方法更合理。

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