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Titlebook: Applications of Fuzzy Techniques; Proceedings of the 2 Scott Dick,Vladik Kreinovich,Pawan Lingras Conference proceedings 2023 The Editor(s)

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,Data Driven Level Set Method in Fuzzy Modeling and Forecasting,is used to model a nonlinear system, and to forecast a time series of actual electricity load data. Computational experiments show that the data-driven level set method outperforms state of the art machine learning algorithms.
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2367-3370 dings of the 2022 Annual Conference of the North American Fu.This book is of interest to practitioners, researchers and graduate students seeking to apply existing techniques, to learn about the state of the art, or to explore novel concepts, in the theory and application of fuzzy sets and logic. Hu
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https://doi.org/10.1007/978-1-4615-0521-1ilar results than its probabilistic counterpart i.e. to have aperiodic limiting distributions and convergence in finite–time unlike the fuzzy . relation which mostly leads to non–unique solutions i.e. periodic limiting distributions.
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https://doi.org/10.1007/978-1-4615-1193-9ation increases and requires additional computations. In this paper we address the problem of random variate generation of fuzzy linguistic variables under the . operator which is useful in linguistic reasoning.
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Flutter Mitigation via Fuzzy Gain Scheduling of a Passivity-Based Controller,chnology model simulates flutter for control design purposes. Passivity-based control is chosen for its desirable robustness properties and physical motivation. A Fuzzy Gain Scheduling approach is used to achieve improved performance by varying gains with the operating condition. The fuzzy gain schedule is tuned by a Genetic Algorithm.
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,An Experimental Study on Fuzzy Markov Chains Under , Generalized Mean Relation,ilar results than its probabilistic counterpart i.e. to have aperiodic limiting distributions and convergence in finite–time unlike the fuzzy . relation which mostly leads to non–unique solutions i.e. periodic limiting distributions.
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