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Fuzzy logic research work in Mexico motivated by Lotfi Zadeh

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Title of paper: Fuzzy logic research work in Mexico motivated by Lotfi Zadeh
Author(s):
Oscar Castillo
Tijuana Institute of Technology, Tijuana, Mexico
Patricia Melin
Tijuana Institute of Technology, Tijuana, Mexico
Published in: Notes on Intuitionistic Fuzzy Sets, Volume 27 (2021), Number 2, pages 1–10
DOI: https://doi.org/10.7546/nifs.2021.27.2.1-10
Download:  PDF (669  Kb, Info)
Abstract: We provide in this article a short review of the research work that has been done in Mexico on developing new methods and theory for designing intelligent systems utilizing type-2 fuzzy systems in combination with soft computing techniques. Soft Computing (SC) is an area formed by intelligent paradigms, like fuzzy systems, neural networks, and bio-inspired and swarm algorithms, which may be utilized to build high performance hybrid systems. The combination of type-2 fuzzy systems with SC enables the constructing of efficient intelligent systems for solving complex problems in a wide diversity of areas, such as control, pattern recognition, medical diagnosis and others. We also recall some of the main moments and memories of encounters and meetings with the father of fuzzy logic (Prof. L. Zadeh), which were very positive and motivated us to continue his work and legacy.
Keywords: Fuzzy logic, Type-2 fuzzy logic, Fuzzy systems.
References:
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  17. González, B., Valdez, F., Melin, P., & Prado-Arechiga, G. (2015). Fuzzy logic in the gravitational search algorithm enhanced using fuzzy logic with dynamic alpha parameter value adaptation for the optimization of modular neural networks in echocardiogram recognition. Applied Soft Computing 37, 245-–254.
  18. Miramontes, I., Guzman, J., Melin, P., & Prado-Arechiga, G. (2018). Optimal Design of Interval Type-2 Fuzzy Rate Level Classification Systems Using the Bird Swarm Algorithm. Algorithms, 11 (12), 206.
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  20. Sánchez, D., & Melin, P. (2014). Optimization of modular granular neural networks using hierarchical genetic algorithms for human recognition using the ear biometric measure. Engineering Applications of Artificial Intelligence, 27, 41–56.
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