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Mamdani FLC with Various Implications
2009 11th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, 2009The task of the standard Mamdani fuzzy logic controller is to find a crisp control action from the fuzzy rule-base and from a set of crisp inputs. Because the interval inputs are frequently used in various domains (online shopping, for instance), in this paper we propose an extension of this type of controller which works with intervals as inputs and ...
Ion Iancu, Mihaela Colhon
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The continuity of Mamdani method
Proceedings. International Conference on Machine Learning and Cybernetics, 2003In this paper the continuity of fuzzy reasoning method is proposed and the usually used Mamdani method of fuzzy reasoning method is proved to be continuous with respect to some distances of fuzzy sets.
null Min Liu +2 more
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Sugeno, Mamdani, and fuzzy Mamdani controllers put in a uniform interpolation framework
International Journal of Intelligent Systems, 1998The paper provides a general framework for proving that fuzzy controllers are universal approximators. The proposed approach is constructive meaning that one is provided with a constructive proof (method) of designing the required fuzzy controllers. Several main classes of commonly encountered fuzzy controllers (Sugeno-Takagi, Mamdani) are analyzed in ...
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Algebraic operations on a class of Mamdani-controllers
Fuzzy Sets and Systems, 1999zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ekkehard Hennebach, Werner Dilger
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Neurofuzzy Approximator based on Mamdani’s Model
2002Neurofuzzy approximators can take on numerous alternatives, as a consequence of the large body of options available for defining their basic operations. In particular, the extraction of the rules from numerical data can be conveniently based on clustering algorithms. The large number of clustering algorithms introduces a further flexibility. Neurofuzzy
FRATTALE MASCIOLI, Fabio Massimo +4 more
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Successive Overrelaxation for Mamdani Fuzzy Systems
Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007), 2007To design a Mamdani fuzzy system with good generalization ability in high dimensional feature space, a novel learning algorithm based on the structural risk minimization (SRM) inductive principle is presented in this paper. Firstly, the parameter estimation of a Mamdani fuzzy system is converted to a quadratic optimization problem.
Qianfeng Cai +2 more
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On Takagi Sugeno approximations of Mamdani fuzzy systems
2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS), 2016In the present paper we propose, and investigate different constructive approaches to approximate Mamdani fuzzy systems, using Takagi-Sugeno systems. The Takagi- Sugeno fuzzy systems that we construct will be based on a piecewise linear approximation, an interpolation polynomial, and an approach based on cubic splines. Since using a Mamdani system with
Salem B. Bacha, Barnabás Bede
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How to improve mamdani's approach to fuzzy control
International Journal of Intelligent Systems, 1995Fuzzy control is a methodology that translates “if”-“then” rules, Aji (x1) &…& Ajn(xn) Bj(u), formulated in terms of a natural language, into an actual control strategy u(x). Implication of uncertain statements is much more difficult to understand than “and,” “or,” and “not.” So, the fuzzy control methodologies usually start with translating “if”-“then”
Bo Friesen, Vladik Kreinovich
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