Fuzzy interpolative reasoning based on the ratio of fuzziness of rough-fuzzy sets

Author:

Chen Shyi-Ming,Cheng Shou-Hsiung,Chen Ze-Jin

Funder

Ministry of Science and Technology, Republic of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference69 articles.

1. Roughness of a fuzzy set;Banerjee;Inform. Sci.,1996

2. A generalized concept for fuzzy rule interpolation;Baranyi;IEEE Trans. Fuzzy Syst.,2004

3. P. Baranyi, D. Tikk, Y. Yam, L.T. Koczy, A new method for avoiding abnormal conclusion for α-cut based rule interpolation, in: Proceedings of 1999 IEEE International Conference on Fuzzy Systems, Seoul, Korea, 1999, pp. 383–388.

4. B. Bouchon-Meunier, C. Marsala, M. Rifqi, Interpolative reasoning based on graduality, in: Proceedings of 2000 IEEE International Conference on Fuzzy Systems, San Antonio, Texas, U.S.A., 2000, pp. 483–487.

5. A hybrid learning algorithm for a class of interval type-2 fuzzy neural networks;Castro;Inform. Sci.,2009

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