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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)90216-0Search in Google Scholar

Calvo, T., Mayer, G. and Mesiar, R. (2002). Aggregation Operators: New Trends and Applications, Physica-Verlag, Heidelberg/New York, NY.10.1007/978-3-7908-1787-4Search 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)90027-1Search 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.2003.10.038Search 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.2011.2170428Search 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_10Search 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.2012.05.028Search in Google Scholar

Hohle, U. (1978). Probabilistic uniformization of fuzzy topologies, Fuzzy Sets and Systems 1(4): 311-332.10.1016/0165-0114(78)90021-0Search in Google Scholar

Klement, E.P.,Mesiar, R. and Pap, E. (2000). Triangular Norms, Kluwer Academic Publishers, Dordrecht.10.1007/978-94-015-9540-7Search 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.2003.06.007Search 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)00327-0Search 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_34Search 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-ySearch 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.2006.10.00517129582Search 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.2008.06.005Search 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.2008.09.015Search 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.2010.09.133Search 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.2012.08.014Search 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.2005.05.00816159657Search 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.28.12.535107853416588583Search 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.2006.890687Search in Google Scholar

Schweizer, B. and Sklar, A. (1960). Statistical metric spaces, Pacific Journal of Mathematics 10(1): 313-334.10.2140/pjm.1960.10.313Search 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): 449-508.10.2174/1574893608666131231231238Search 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.12010Search 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_9Search 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. 10.1109/21.87068Search in Google Scholar

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Sujets de la revue:
Mathematics, Applied Mathematics