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A Novel Fuzzy Logic System with Consequents as Fuzzy Weighted Averages of Antecedents

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Proceedings of 2018 Chinese Intelligent Systems Conference

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 529))

Abstract

Fuzzy logic system is an intelligent system based on IF-THEN rules, which can handle uncertainties effectively, and has been applied to various fields. The design of rules is a key step when a fuzzy logic system is modelled in a practical situation. In this paper, a novel fuzzy logic system named FWA with novel rules is proposed, in which the consequents are fuzzy weighted averages of antecedents. The proposed rules establish some relationship between consequents and antecedents in advance, so that the proposed FWA fuzzy logic system will reduce training time, improve training efficiency, and optimize parameters faster.

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Acknowledgements

This work is supported by National Natural Science Foundation of China (61403011).

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Authors and Affiliations

  1. School of Mathematics and Systems Science and LMIB of the Ministry of Education, Beihang University, Beijing, 100191, China

    Qiye Zhang, Yuqing Liu & Xiao Tian

Authors
  1. Qiye Zhang
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  2. Yuqing Liu
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  3. Xiao Tian
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Corresponding author

Correspondence to Yuqing Liu .

Editor information

Editors and Affiliations

  1. Beihang University, Beijing, China

    Yingmin Jia

  2. Beijing University of Posts and Telecommunications, Beijing, China

    Junping Du

  3. University of Science and Technology Beijing, Beijing, China

    Weicun Zhang

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Zhang, Q., Liu, Y., Tian, X. (2019). A Novel Fuzzy Logic System with Consequents as Fuzzy Weighted Averages of Antecedents. In: Jia, Y., Du, J., Zhang, W. (eds) Proceedings of 2018 Chinese Intelligent Systems Conference. Lecture Notes in Electrical Engineering, vol 529. Springer, Singapore. https://doi.org/10.1007/978-981-13-2291-4_56

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