Fuzzy-Membership-Kernel Learning Based on Takagi–Sugeno Models

Author:

Wang Jianmin,Kang Mingxin

Publisher

Springer Science and Business Media LLC

Reference23 articles.

1. Mahesh, P.V., Meyyappan, S., Alla, R.: Support vector regression machine learning based maximum power point tracking for solar photovoltaic systems. Int. J. Electr. Comput. Eng. Syst. 14(1), 100–108 (2023)

2. Varshney, A.K., Torra, V.: Literature review of the recent trends and applications in various fuzzy rule-based systems. Int. J. Fuzzy Syst. 25, 2163–2186 (2023)

3. Schölkopf, B., Smola, A.J.: Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. MIT Press, Cambridge (2002)

4. Wolpert, D.H.: The lack of a priori distinctions between learning algorithms. Neural Comput. 8(7), 1341–1390 (1996)

5. Sevakula, R.K., Verma, N.K.: Compounding general purpose membership functions for fuzzy support vector machine under noisy environment. IEEE Trans. Fuzzy Syst. 25(6), 1446–1459 (2017)

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