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Rule base and adaptive fuzzy operators cooperative learning of Mamdani fuzzy systems with multi-objective genetic algorithms., , and . Evolutionary Intelligence, 2 (1-2): 39-51 (2009)The NAO models for the elderly., , , and . HRI, page 187-188. IEEE/ACM, (2013)An efficient multi-objective evolutionary adaptive conjunction for high dimensional problems in linguistic fuzzy modelling., , and . FUZZ-IEEE, page 1-8. IEEE, (2012)Evolutionary Design of Linguistic Fuzzy Regression Systems with Adaptive Defuzzification in Big Data Environments., , , and . Cognitive Computation, 11 (3): 388-399 (2019)Playification: The PhySeEar case., , , and . CHI PLAY, page 376-388. ACM, (2016)A Mechanism to Improve the Interpretability of Linguistic Fuzzy Systems with Adaptive Defuzzification based on the use of a Multi-objective Evolutionary Algorithm., , and . Int. J. Comput. Intell. Syst., 5 (2): 297-321 (2012)Cooperation between the Inference System and the Rule Base by Using Multiobjective Genetic Algorithms., , and . HAIS, volume 5271 of Lecture Notes in Computer Science, page 739-746. Springer, (2008)PhySeEar Moving yourself to shine and sound in geriatric physiotherapy interventions., , and . PervasiveHealth, page 179-182. IEEE, (2012)A multi-objective evolutionary algorithm with an interpretability improvement mechanism for linguistic fuzzy systems with adaptive defuzzification., , and . FUZZ-IEEE, page 1-7. IEEE, (2010)A scalable evolutionary linguistic fuzzy system with adaptive defuzzification in big data., , and . FUZZ-IEEE, page 1-6. IEEE, (2017)