particular, fuzzy clustering algorithm fuzzy C means clustering (FCM, Fuzzy C-Means) segmentation algorithm, carefully study the image segmentation algorithm based on fuzzy clustering in the number of categories to determine the initial cluster, The initial cluster centers and membership functions of ...
For this reason, fuzzy C-means cluster segmentation algorithm based on bacterial colony chemotaxis (BCC) is proposed in this paper. Firstly, initial cluster centers of FCM algorithm is get by BCC algorithm. Then, the images are segmented using FCM algorithm. Experimental results show that the ...
The FCM algorithm computes cluster centers and membership values to minimize the following objective function. Here: N is the number of data points. C is the number of clusters. To specify this value, use the NumClusters option. m is fuzzy partition matrix exponent for controlling the degree ...
Cluster Analysis Igor Kononenko, Matjaž Kukar, in Machine Learning and Data Mining, 2007 Fuzzy c-means clustering The fuzzy c-means is a fuzzy variant of the k-means partitional algorithm. With fuzzy c-means, the centroid (also called a prototype) of a cluster is computed as being the ...
曲线分割和曲面分割分类问题的3个典型数据集为算例,结果表明该方法能够识别不规则的簇,解决了FCM算法对初始聚类中心敏感的缺陷.关键词模糊C均值聚类算法;对应分析;加权FCM算法;模糊隶属度矩阵;类间分离度;类内紧缩度中图分类号TP181文献标志码A文章编号1671—4512(2012)02—0107—05Studyofmulti--prototypefuzzyC-。
E. & Tsai, C. Y. A hybrid metaheuristic and kernel intuitionistic fuzzy c-means algorithm for cluster analysis. Appl. Soft Comput. 67, 299–308. https://doi.org/10.1016/j.asoc.2018.02.039 (2018). Article Google Scholar Izakian, H. & Abraham, A. Fuzzy C-means and fuzzy swarm for...
Local convergence of the fuzzy c -Means algorithms ☆Cluster analysisFuzzy c-MeansLocal convergencePattern recognitionMuch understanding has recently been gained concerning global convergence properties of the fuzzy c-Means (FCM) family of clustering algorithms. These global convergence properties, which ...
J.C. Bezdek et al. FCM: The fuzzy c-means clustering algorithm Computers & Geosciences (1984) L. Cagnina et al. An efficient particle swarm optimization approach to cluster short texts Information Sciences (2014) H. Izakian et al. Fuzzy c-means and fuzzy swarm for fuzzy clustering problem...
Based on field measured data of joint sets,analysis steps,parameter selection,cluster validity,and determination of dominant direction for identification of the joint sets by the method,are discussed. 展开 关键词: rock mechanics rock mass joint fuzzy C-means cluster algorithm genetic algorithm ...
Using a modified Xie-Beni cluster validity index, the fuzzy c-means cluster algorithm with entropy regularization is extended to integrate fuzzy cluster and density estimation to identify TF components and derive TF energy mixture model that indicates the number of components in the s. 用修正的Xie...