Detroja 等 [14] 建立了模糊相似聚类（fuzzy possibilistic clustering，FPC）诊断方法，根据已知 的历史数据建立知识信息库（knowledge base）， 采用待诊断数据与聚类...
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Firstly, the advantages of fuzzy C-means clustering and possibilistic C-means clustering are utilized in this paper. We design a new hybrid C-means clustering accordingly.
首先该文利用模糊C均值聚类和可能性C均值聚类的优点，设计出一种混合C均值聚类算法。
A new non-Euclidean distance was introduced to replace the Euclidean distance in the IPCM, and then a new fuzzy clustering, called novel improved possibilistic C-means (NIPCM) clustering was proposed.
通过引入一种新的非欧式距离以替代IPCM目标函数中的欧式距离，提出了一种称为新的改进型可能C -均值聚类(NIPCM)算法。
Firstly, the advantages of fuzzy C-means clustering and possibilistic C-means clustering are utilized in this paper.
首先该文利用模糊C均值聚类和可能性C均值聚类的优点，设计出一种混合C均值聚类算法。
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