Bruno A P, Anderson F B F da Costa, Renata M C R de Souza. 2011. Kernel-Based fuzzy clustering of interval data. IEEE Conf Fuzz Syst. 497-501
[9]
Chantal H, Hani H. 2011. Self-Organizing map based on hausdorff distance for Interval-valued data. Ieee T Syst Man Cy. 1747-1752, doi: 10.1109/ICSMC.2011.6083924
[10]
Chuang C C, Jeng J T, Li C W. 2008. Fuzzy C-Means clustering algorithm with unknown number of clusters for symbolic interval data. In: SICE Annual Conference, Tokyo. 358-363
[11]
Francisco de AT de Carvalho. 2007. Fuzzy c-means clustering methods for symbolic interval data. Pattern Recogn Lett, 28: 423-437
[12]
Francisco de A T.de Carvalho. 2006. A fuzzy clustering algorithm for symbolic interval data based on a single adaptive euclidean distance. In: Neural Information Processing, Lecture Notes in Computer Science. 4234: 1012-1021
[13]
Francisco de A T. de Carvalho, Y ves L. 2009. Dynamic Clustering of Interval-Valued Data Based on Adaptive Quadratic Distances. Ieee T Syst Man Cy A, 39: 1295-1306
[14]
Francisco de A T. de Carvalho, Camilo P T. 2010. Fuzzy K-means clustering algorithms for interval-valued data based on adaptive quadratic distances. Fuzzy Set Syst, 161: 2978-2999
[15]
Francisco de A T. de Carvalho, Renata M.C.R. de Souza. 2010. Unsupervised pattern recognition models for mixed feature-type symbolic data. Pattern Recogn Lett, 31: 430-443
[16]
Hani H, Chantal H. 2011. A Neural Networks Approach To Interval-Valued Data Clustering. Application To Lebanese Meteorological Stations Data. IEEE SiPS2011. 373-378
[17]
Liem T, Lucien D. 2002. Comparison of fuzzy numbers using a fuzzy distance measure. Fuzzy Set Syst, 130: 331-341
[18]
Marie Chavent, Francisco de A. T. de Carvalho, Yves Lechevallier, et al. 2006. New clustering methods for interval data. Computation Stat, 21: 211-229
[19]
Peng W, Li T. 2006. Interval Data Clustering with Applications. Tools Art Intell. 355-362, doi: 10.1109/ICTAI.2006.71
[20]
Renata M.C.R. de Souza, Francisco de A.T. de Carvalho. 2004. Clustering of interval data based on city-block distances. Pattern Recogn Lett, 25: 353-365
[21]
Renata M.CR. de Souza, Francisco de A. T. de Carvalho, Camilo P. Tenório, et al. 2004. Dynamic cluster methods for interval data based on mahalanobis distances. Proc 9th conf Fed Class Soci. IV: 351-360