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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This work is supported by National Natural Science Foundation of China (61403011).
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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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DOI: https://doi.org/10.1007/978-981-13-2291-4_56
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