[1] HAN J,KAMBER M,PEI J.Data mining concept and techniques[M].[S.l.]:Morgan Kaufmann,2011. [2] BEZDEK J C.Pattern recognition with fuzzy objective function algorithms[J].Advanced Applications in Pattern Recognition,1981,22(1171):203-239. [3] WANG Xizhao,WANG Yadong,WANG Lijuan.Improving fuzzy C-means clustering based on feature-weight learning[J].Pattern Recognition Letters,2004,25(10):1123-1132. [4] KANNAN S R,DEVI R,RAMATHILAGAM S,et al.Effective FCM noise clustering algorithms in medical images[J].Computers in Biology & Medicine,2013,43(2):73-83. [5] GUEORGUIEVA N,VALOVA I,GEORGIEV G.M&MFCM:fuzzy C-means clustering with Mahalanobis and Minkowski distance metrics[J].Procedia Computer Science,2017,114:224-233. [6] SEAL A,KARLEKAR A,KREJCAR O,et al.Fuzzy C-means clustering using Jeffreys-divergence based similarity measure[J].Applied Soft Computing,2020,88:1-5. [7] KANG Jiayin,JI Zhicheng,GONG Chenglong.Kernelized fuzzy C-means clustering algorithm and its application[J].Chinese Journal of Scientific Instrument,2010,31(7):1657-1663.(in Chinese)康家银,纪志成,龚成龙.一种核模糊C均值聚类算法及其应用[J].仪器仪表学报,2010,31(7):1657-1663. [8] ZENG Shan,TONG Xiaojun,SANG Nong.Study on multi-center fuzzy C-means algorithm based on transitive closure and spectral clustering[J].Applied Soft Computing,2014,16:89-101. [9] TAO Xinmin,WANG Ruotong,CHANG Rui,et al.Spectral clustering algorithm using density-sensitive distance measure with global and local consistencies[J].Knowledge-Based Systems,2019,170:26-42. [10] FREY B J,DUECK D.Clustering by passing messages between data points[J].Science,2007,315(5814):972-976. [11] SUBBALAKSHMI C,KRISHNA G R,RAO S K M,et al.A method to find optimum number of clusters based on fuzzy silhouette on dynamic data set[J].Procedia Computer Science,2015,46:346-353. [12] ESTIRI H,OMRAN B A,MURPHY S N.kluster:an efficient scalable procedure for approximating the number of clusters in unsupervised learning[J].Big Data Research,2018,13:38-51. [13] ZHU Erzhou,ZHANG Yuanxiang,WEN Peng,et al.Fast and stable clustering analysis based on grid-mapping K-means algorithm and new clustering validity index[J].Neurocomputing,2019,363:149-170. [14] PHAM V N,NGO L T,PEDRYCZ W.Interval-valued fuzzy set approach to fuzzy Co-clustering for data classification[J].Knowledge-Based Systems,2016,107:1-13. [15] HANMANDLU M,VERMA O P,SUSAN S,et al.Color segmentation by fuzzy co-clustering of chrominance color features[J].Neurocomputing,2013,120:235-249. [16] de AMORIM R C,HENNIG C.Recovering the number of clusters in data sets with noise features using feature rescaling factors[J].Information Sciences,2015,324:126-145. [17] LING Huilinag,WU Jiansheng,ZHOU Yi,et al.How many clusters?A robust pso-based local density model[J].Neurocomputing,2016,207:264-275. [18] CHENG Weiqing,LU Yanhong.Adaptive clustering algorithm based on maximum and minimum distances and SSE[J].Journal of Nanjing University of Posts and Telecommunications(Natural Science Edition),2015,35(2):102-107.(in Chinese)成卫青,卢艳红.一种基于最大最小距离和SSE的自适应聚类算法[J].南京邮电大学学报(自然科学版),2015,35(2):102-107. [19] FREY B J,DUECK D.Response to comment on "clustering by passing messages between data points"[J].Science,2008,319(5864):726-726. [20] WANG Kaijun,LI Jian,ZHANG Junying,et al.Semi-supervised affinity propagation clustering[J].Computer Engineering,2007,33(23):197-198,201.(in Chinese)王开军,李健,张军英,等.半监督的仿射传播聚类[J].计算机工程,2007,33(23):197-198,201. [21] SUN Jixiang.Modern pattern recognition[M].Changsha:National University of Defense Technology,2002.(in Chinese)孙即祥.现代模式识别[M].长沙:国防科技大学出版社,2002. [22] RODRIGUEZ A,LAIO A.Clustering by fast search and find of density peaks[J].Science,2014,344(6191):1492-1496. [23] WU T F,TSAI P S,HU N T,et al.Combining turning point detection and Dijkstra's algorithm to search the shortest path[J].Advances in Mechanical Engineering,2017,9(2):1-12. [24] MACQUEEN J.Some methods for classification and analysis of multivariate observations[C]//Proceedings of the 5th Berkeley Symposium on Mathematical Statistics and Probability.Berkeley,USA:University of California Press,1967:281-297. [25] SHANG Fanhua,JIAO Licheng,SHI Jiarong,et al.Fast affinity propagation clustering:a multilevel approach[J].Pattern Recognition,2012,45(1):474-486. [26] VINH N X,EPPS J,BAILEY J.Bibliometrics:information theoretic measures for clusterings comparison[C]//Proceedings of International Conference on Machine Learning.New York,USA:ACM Press,2010:2837-2854. |