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Mechanisms of Mixed Fuzzy Reasoning for Asymmetric Types

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Quantitative Logic and Soft Computing 2016

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 510))

Abstract

In the basic models of fuzzy reasoning, the fuzzy propositions are the same type of fuzzy sets. In the paper, we intend to investigate the inference mechanisms of mixed fuzzy reasoning for asymmetric types such that the fuzzy propositions are the different type of fuzzy sets. We establish the two new models for the asymmetric type approximate reasoning problems and present the corresponding methods to solve the new models. Furthermore, we analyze the characterizations of the solutions and give their reductivity.

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Acknowledgments

The authors acknowledge their supports from the National Natural Science Foundation of China (Nos. 11401361, 61473336, 61572016).

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Correspondence to Mu-Cong Zheng .

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Liu, Y., Zheng, MC. (2017). Mechanisms of Mixed Fuzzy Reasoning for Asymmetric Types. In: Fan, TH., Chen, SL., Wang, SM., Li, YM. (eds) Quantitative Logic and Soft Computing 2016. Advances in Intelligent Systems and Computing, vol 510. Springer, Cham. https://doi.org/10.1007/978-3-319-46206-6_29

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  • DOI: https://doi.org/10.1007/978-3-319-46206-6_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46205-9

  • Online ISBN: 978-3-319-46206-6

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