[2] ZHAO Chunhui,QI Bin. Hyperspectral image classification based on fuzzy kernel weighted c-means clustering [J]. Chinese Journal of Scientific Instrument,2012,33(9):2016-2021.
[3] LI Qiaolan. Semi-supervised clustering based on constraints for image segmentation [D]. Xi′an:Xidian University,2014:1-2.
[4] LENG Mingwei. Research of active semi-supervised clustering and its application in community detection [D]. Lanzhou: Lanzhou University,2014:14-23.
[5] CHEN Xiaodong,YIN Xuesong,LIN Huanxiang. Semi-supervised clustering approach with discriminant analysis [J]. Computer Engineering and Applications,2010,46(6):139-143.
[6] Camps-Valls Gustavo,Marsheva Tatyana V. Bandos,ZHOU Dengyong. Semi-supervised graph-based hyperspectral image classification [J]. IEEE Transactions on Geoscience and Remote Sensing(S0196-2892),2007,45(10):3044-3054.
[8] Papadopoulos Dimitris F,Simos Theodore E. A modified runge-kutta-nystr.m method by using phase lag properties for the numerical solution of orbital problems [J]. Applied Mathematics & Information Sciences(S1935-0090),2013,7(2):433-437.
[9] XIE Juanying,GUO Wenjuan,XIE Weixin,et al. K-means clustering algorithm based on optimal initial centers related to pattern distribution of samples in space [J]. Applications Research of Computers,2012,29(3):888-892.
[10] WANG Feng,JI Jincheng,NIE Baisheng. An improved fusion method of fuzzy logic based on k-mean clustering [J]. Journal of North University of China:Natural Science Edition,2014,35(6):699-703.
[11] ZHANG Huizhe,WANG Jian. Improved fuzzy c-means clustering algorithm based on selecting initial clustering centers [J]. Computer Science,2009,36(6):206-209.
[12] Kannan S R,Ramathilagam S. Effective fuzzy c-means clustering algorithms for data clustering problems [J]. Expert Systems with Applications(S0957-4174),2012,39(7):6292–6300.
[13] ZHAO Weizhong,HE Qing,MA Huifang. Effective semi-supervised document clustering via active learning with instance-level constraints [J]. Knowledge & Information Systems(S0219-1377),2012,30(3):569-587.
[14] Ozer Sedat,CHEN Chi H. A set of new chebyshev kernel function for support vector machine pattern classification [J]. Pattern Recognition(S0031-3203),2011,44(7):1435-1447.
[15] ZHANG Rui,WANG Wenjian. Facilitating the application of support vector machine by using a new kernel [J]. Export Systems with Applications(S0957-4174),2011,38(11):14225-14230.