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Performance analysis of fuzzy systems based on quintuple implications method

机译:基于五重蕴涵方法的模糊系统性能分析

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摘要

To improve the quality of approximate reasoning in fuzzy system, quintuple implication principle (QIP) to resolve fuzzy modus ponens (FMP) and fuzzy modus tollens (FMT) problems has been proposed by Zhou et al. [32]. The same approximation as Mamdani-type fuzzy inference can be reached by fuzzy reasoning with QIP method for Godel implication. It therefore is essential to establish some fundamental properties of fuzzy inference system with QIP method. This paper mainly investigates the robustness and universal approximation capability of fuzzy inference system with QIP method. Firstly, we present the QIP solutions of FMP and FMT for R-, S-, QL-, f- and g-implications. And then the robustness of fuzzy inference system with QIP method is discussed. Finally, we study the universal approximation properties of multiple-input and single-output (MISO) fuzzy systems with QIP method for R-, S- and QL-implications. These results reveal that the OIP method possesses better performance in fuzzy rule-based system. (C) 2018 Elsevier Inc. All rights reserved.
机译:为了提高模糊系统中近似推理的质量,Zhou等人提出了五元蕴涵原理(QIP)来解决模糊模态量(FMP)和模糊模量收费(FMT)的问题。 [32]。可以通过QIP方法对Godel蕴涵进行模糊推理,获得与Mamdani型模糊推理相同的近似值。因此,利用QIP方法建立模糊推理系统的一些基本特性至关重要。本文主要研究了采用QIP方法的模糊推理系统的鲁棒性和通用逼近能力。首先,我们针对R-,S-,QL-,f-和g蕴涵提出FMP和FMT的QIP解决方案。然后讨论了基于QIP方法的模糊推理系统的鲁棒性。最后,我们使用R,S和QL蕴涵的QIP方法研究了多输入和单输出(MISO)模糊系统的通用逼近性质。这些结果表明,OIP方法在基于模糊规则的系统中具有更好的性能。 (C)2018 Elsevier Inc.保留所有权利。

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