Fuzzy Logic and Computational Intelligence
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This reprint contains 11 articles that were accepted and published in the Special Issue "Fuzzy Logic and Computational Intelligence" of the MDPI Mathematics journal. It covers a wide range of topics connected to the theory and applications of fuzzy logic approaches, which extracts high-level knowledge from data to improve system performance. This high-level extracted knowledge is learned using machine learning models to design computationally high intelligent systems. This learning mechanism could be made better by implementing optimization techniques that mimic the behavior of representatives...
This reprint contains 11 articles that were accepted and published in the Special Issue "Fuzzy Logic and Computational Intelligence" of the MDPI Mathematics journal. It covers a wide range of topics connected to the theory and applications of fuzzy logic approaches, which extracts high-level knowledge from data to improve system performance. This high-level extracted knowledge is learned using machine learning models to design computationally high intelligent systems. This learning mechanism could be made better by implementing optimization techniques that mimic the behavior of representatives or groups. Simply put, they adopt the ways in which individuals exchange and analyze information cooperatively to achieve a particular goal or to make a decision. This reprint provides the readers with extensive explorations of recent advances in computing, intelligent systems, and fuzzy applications. The recent development of real-world applications that are practical and pragmatic make this reprint valuable to the academic community and expert industry practitioners. The purpose of this reprint is to deliver quality novel and unpublished work in the domains of pattern recognition, decision systems, the optimization of complex problems, medical diagnosis, and robotics and intelligent control systems.
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