[1]PEDRYCZ W. Conditional fuzzy C-means [J]. Pattern Recognition Letters, 1996, 17(6): 625-631.[2]GRAVES D, PEDRYCZ W. Kernel-based fuzzy clustering and fuzzy clustering: A comparative experimental study [J]. Fuzzy Sets and Systems, 2010, 161(4): 522-543.[3]SONG Q, YANG X L, SOH Y C, et al. An information-theoretic fuzzy C-spherical shells clustering algorithm[J]. Fuzzy Sets and Systems, 2010, 161(13): 1755-1773.[4]LEE M, PEDRYCZ W. The fuzzy C-means algorithm with fuzzy P-mode prototypes for clustering objects having mixed features[J]. Fuzzy Sets and Systems, 2009, 160(24): 3590-3600.[5]刘小芳,曾黄麟,吕炳朝. 点密度函数加权模糊C-均值算法的聚类分析[J]. 计算机工程与应用,2004,40(24):64-65.[6]TANG C L, WANG S G, XU W. New fuzzy C-means clustering model based on the data weighted approach [J]. Data & Knowledge Engineering, 2010, 69(9): 881-900.[7]王惠,申石磊. 一种改进的特征加权K-means聚类算法[J]. 微电子学与计算机,2010,27(7):161-163.[8]李丹,顾宏,张立勇. 基于属性权重区间监督的模糊C均值聚类算法[J]. 控制与决策,2010,25(3):457-460.[9]BAI L, LIANG J Y, DANG C Y, et al. A novel attribute weighting algorithm for clustering high-dimensional categorical data[J]. Pattern Recognition, 2011, 44(12): 2843-2861.[10]蔡静颖,谢福鼎,张永. 基于自适应马氏距离的模糊C均值算法[J]. 计算机工程与应用,2010,46(34):174-176.[11]XIANG S M, NIE F P, ZHANG C S. Learning a Mahalanobis distance metric for data clustering and classification[J]. Pattern Recognition, 2008, 41(12): 3600-3612.[12]王骏,王士同. 基于混合距离学习的双指数模糊C均值算法[J]. 软件学报,2010,21(8):1878-1888.[13]TSAI D M, LIN C C. Fuzzy C-means based clustering for linearly and nonlinearly separable data[J]. Pattern Recognition, 2011, 44(8): 1750-1760.[14]于迪,李义杰. 基于减法聚类改进的模糊C均值算法的模糊聚类研究[J]. 微型机与应用,2010,29(16):14-16.[15]李雷,罗红旗,丁亚丽. 自适应约束模糊C均值聚类算法[J]. 模糊系统与数学,2010,24(5):126-130.[16]YU J, CHENG Q S, HUANG H K. Analysis of the weighting exponent in the FCM[J]. IEEE Transactions on System, Man and Cybernetics: Part B: Cybernetics, 2004, 34(1): 634-639.[17]肖满生,阳娣兰,张居武,等. 基于模糊相关度的模糊C均值聚类加权指数研究[J]. 计算机应用,2010,30(12):3388-3390. |