[Alsina, C., Trillas, E. and Valverde, L. (1983). On some logical connectives for fuzzy set theory, Mathematical Analysis and Applications 93(1): 15-26.10.1016/0022-247X(83)90216-0]Search in Google Scholar
[Calvo, T., Mayer, G. and Mesiar, R. (2002). Aggregation Operators: New Trends and Applications, Physica-Verlag, Heidelberg/New York, NY.10.1007/978-3-7908-1787-4]Search in Google Scholar
[Detyniecki, M. (2000). Mathematical Aggregation Operators and Their Application to Video Querying, Ph.D. thesis, University of Paris, Paris.]Search in Google Scholar
[Dubois, D. and Prade, H. (1985). A review of fuzzy sets aggregation connectives, Information Sciences 36(1): 85-121.10.1016/0020-0255(85)90027-1]Search in Google Scholar
[Dubois, D. and Prade, H. (2004). On the use of aggregation operations in information fusion processes, Fuzzy Sets and Systems 142(1): 143-161.10.1016/j.fss.2003.10.038]Search in Google Scholar
[Duda, R., Hart, P. and Stork, G.D. (1973). Pattern Classification and Scene Analysis, John Wiley and Sons, New York, NY.]Search in Google Scholar
[Ezghari, S., Belghini, N., Zahi, A. and Zarghili, A. (2015). A gender classification approach based on 3D depth-radial curves and fuzzy similarity based classification, Intelligent Systems and Computer Vision Conference, Fez, Morocco, pp. 1-6.]Search in Google Scholar
[Fengqiu, L. and Xiaoping, X. (2012a). Constructing kernels by fuzzy rules for support vector regressions, International Journal of Innovative Computing, Information and Control 8(7): 4811-4822.]Search in Google Scholar
[Fengqiu, L. and Xiaoping, X. (2012b). Design of natural classification kernels using prior knowledge, IEEE Transactions on Fuzzy Systems 20(1): 135-152.10.1109/TFUZZ.2011.2170428]Search in Google Scholar
[Gabryel, M., Korytkowski, M., Pokropinska, A., Scherer, R. and Drozda, S. (2010). Evolutionary Learning for Neuro- Fuzzy Ensembles with Generalized Parametric Triangular Norms, Springer-Verlag, Berlin/Heidelberg.10.1007/978-3-642-13208-7_10]Search in Google Scholar
[Gil, G., Girela, L.J., De Juan, J., Gomez-Torres, J.M. and Johnsson, M. (2012). Predicting seminal quality with artificial intelligence methods, Expert Systems with Applications 39(16): 12564-12573.10.1016/j.eswa.2012.05.028]Search in Google Scholar
[Hohle, U. (1978). Probabilistic uniformization of fuzzy topologies, Fuzzy Sets and Systems 1(4): 311-332.10.1016/0165-0114(78)90021-0]Search in Google Scholar
[Klement, E.P.,Mesiar, R. and Pap, E. (2000). Triangular Norms, Kluwer Academic Publishers, Dordrecht.10.1007/978-94-015-9540-7]Search in Google Scholar
[Klement, E.P.,Mesiar, R. and Pap, E. (2003a). Triangular norms, Position paper I: Basic analytical and algebraic properties, Fuzzy Sets and Systems 143(1): 5-26.10.1016/j.fss.2003.06.007]Search in Google Scholar
[Klement, E.P.,Mesiar, R. and Pap, E. (2003b). Triangular norms, Position paper II: General constructions and parametrized families, Fuzzy Sets and Systems 145(3): 411-438.10.1016/S0165-0114(03)00327-0]Search in Google Scholar
[Klir, G.J. and Folger, T.A. (1988). Fuzzy Sets, Uncertainty and Information, Prentice Hall, Englewood Cliffs, NJ.]Search in Google Scholar
[Klir, G.J. and Yuan, B. (1995). Fuzzy Sets and Fuzzy Logic: Theory and Applications, Prentice Hall, Englewood Cliffs, NJ.]Search in Google Scholar
[Korytkowski, M. and Scherer, R. (2010). Modular Neurofuzzy Systems Based on Generalized Parametric Triangular Norms, Springer-Verlag, Berlin/Heidelberg.10.1007/978-3-642-14390-8_34]Search in Google Scholar
[Łukasiewicz, J. (1970). Selected Works, North Holland, Amsterdam/London.]Search in Google Scholar
[Li, P. and Fang, S.C. (2008). On the resolution and optimization of a system of fuzzy relational equations with sup-t composition, Fuzzy Optimization Decision Making 7(2): 169-214.10.1007/s10700-008-9029-y]Search in Google Scholar
[Luukka, P. (2005). Similarity Measure Based Classification, Ph.D. thesis, Lappeenranta University of Technology, Lappeenranta.]Search in Google Scholar
[Luukka, P. (2007). Similarity classifier using similarity measure derived from Yu’s norms in classification of medical data sets, Computers in Biology and Medicine 37(7): 1133-1140.10.1016/j.compbiomed.2006.10.00517129582]Search in Google Scholar
[Luukka, P. (2008). Similarity classifier using similarities based on modified probabilistic equivalence relations, Knowledge Based Systems 22(1): 57-62.10.1016/j.knosys.2008.06.005]Search in Google Scholar
[Luukka, P. (2009). Classification based on fuzzy robust PCA algorithms and similarity classifier, Expert Systems with Applications 36(4): 7463-7468.10.1016/j.eswa.2008.09.015]Search in Google Scholar
[Luukka, P. (2011). Feature selection using fuzzy entropy measures with similarity classifier, Expert Systems with Applications 38(4): 4600-4607.10.1016/j.eswa.2010.09.133]Search in Google Scholar
[Luukka, P. and Kurama, O. (2013). Similarity classifier with ordered weighted averaging operators, Expert Systems with Applications 40(4): 995-1002.10.1016/j.eswa.2012.08.014]Search in Google Scholar
[Luukka, P. and Leppalampi, T. (2006). Similarity classifier with generalized mean applied to medical data, Computers in Biology and Medicine 36(9): 1026-1040.10.1016/j.compbiomed.2005.05.00816159657]Search in Google Scholar
[Luukka, P., Saastamoinen, K. and Kononen, V. (2001). A classifier based on the maximal fuzzy similarity in the generalized Łukasiewicz structure, Proceedings of the FUZZ-IEEE 2001 Conference, Melbourne, Australia, pp. 195-198.]Search in Google Scholar
[Mattila, J.K. (2002). Fuzzy Logic Course Book, Art House, Helsinki, (in Finnish).]Search in Google Scholar
[Menger, K. (1942). Statistical metrics, Proceedings of the National Academy of Sciences of the United States of America 28(12): 535-537.10.1073/pnas.28.12.535107853416588583]Search in Google Scholar
[Newman, D.J., Hettich, S., Blake, C.L. and Merz, C.J. (2012). UCI Repository of Machine Learning Databases, www.ics.uci.edu/˜{}mlearn/MLRepository.html.]Search in Google Scholar
[O’Hagan, M. (1988). Aggregating template or rule antecedents in real time expert systems with fuzzy set logic, Proceedings of the 22nd Annual IEEE Asilomar Conference on Signals, Systems, Computers, Pacific Grove, CA, USA, pp. 681-689.]Search in Google Scholar
[Saminger, P.S., Mesier, R. and Dubois, D. (2007). Aggregation operators and commuting, IEEE Transactions on Fuzzy Systems 15(6): 1032-1045.10.1109/TFUZZ.2006.890687]Search in Google Scholar
[Schweizer, B. and Sklar, A. (1960). Statistical metric spaces, Pacific Journal of Mathematics 10(1): 313-334.10.2140/pjm.1960.10.313]Search in Google Scholar
[Schweizer, B. and Sklar, A. (1983). Probabilistic Metric Spaces, North-Holland, New York, NY.]Search in Google Scholar
[Sivaramakrishnan, R. and Arun, C. (2014). Classification of Denver systems of chromosomes using similarity classifier guided by OWA operators, Current Bioinformatics 9(5): 449-508.10.2174/1574893608666131231231238]Search in Google Scholar
[Turunen, E. (2002). Mathematics Behind Fuzzy Logic, Physic-Verlag, Heidelberg.]Search in Google Scholar
[Vlahogianni, E. and Karlaftis, M.G. (2013). Fuzzy-entropy neural network freeway incident duration modeling with single and competing uncertainties, Computer-aided Civil and Infrastructure Engineering 28(6): 420-433.10.1111/mice.12010]Search in Google Scholar
[Xu, Z.S. (2008). Linguistic aggregation operators: An overview, Fuzzy Sets and Their Extension, Representation, Aggregation and Models 220(1): 163-181.10.1007/978-3-540-73723-0_9]Search in Google Scholar
[Yager, R.R. (1988). On ordered weighted averaging aggregation operators in multi-criteria decision making, IEEE Transactions on Systems, Man and Cybernetics, 18(1): 183-190. 10.1109/21.87068]Search in Google Scholar