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Limitations of quantitative operator fuzzy logic

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Abstract

Quantitative models of operator fuzzy logic are discussed. It is proved that there is a unique real polynomial function that can be used to characterize the composition operation between fuzzy operators in a quantitative model of operator fuzzy logic. Based on this polynomial function, we redefine a new quantitative operator fuzzy logic NOFL by revising the existing suggested alternatives. It can be seen that it is hard for a quantitative model of operator fuzzy logic to be both theoretically sound and intuitively acceptable.

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References

  1. Liu, X. H., Xiao, H., Operator fuzzy logic and fuzzy resolution, inProc. of 15th ISMVL, Kingston, Canada, May 1985, Silver Spring: IEEE Comput. Soc. Press, 1985, 68–75.

    Google Scholar 

  2. Liu, X. H., Xiao, H., Operator fuzzy logic and λ-resolution,Chinese J. of Computers (in Chinese), 1989, 12(2): 81.

    Google Scholar 

  3. Liu, X.H., An, Z., An improvement of operator fuzzy logic and its resolution deduction,Chinese J. of Computers (in Chinese), 1990, 13(12): 890.

    Google Scholar 

  4. Cheng, X.C., Liu, X.H., Lu, R.Q., The operator fuzzy logics based on evidence considerations,Chinese Science Bulletin (in Chinese), 1995, 40(2): 185.

    MathSciNet  Google Scholar 

  5. Liu, X.H., Fang, K.Y., Tsai, J.P., et al., λ-Resolution and interpretation of λ-implication in fuzzy operator logic,Information Sciences, 1991, 56(1–3): 256.

    MathSciNet  Google Scholar 

  6. Tsai, J.P., Weigert, T., Liu, X.H., Reasoning under uncertainty in fuzzy operator logic,IEEE Trans. on Systems, Man, and Cybernetics, 1991, 21(6): 1604.

    Article  MATH  Google Scholar 

  7. Liu, X.H., Cheng, X.C., The operator fuzzy logics based on belief considerations,Chinese J. of Computers (in Chinese), 1995, 18(12): 881.

    Google Scholar 

  8. Cheng, X.C., Jiang, Y.F., Liu, X.H., Dialectic operator fuzzy logic,Science in China, Ser. E, 1996, 39(1): 1.

    MATH  MathSciNet  Google Scholar 

  9. Lu, R.Q.,Artificial Intelligence (second half) (in Chinese), Beijing: Science Press, 1996, 599–615.

    Google Scholar 

  10. Lee, R.C.T., Chang, C.L., Some properties of fuzzy logic,Information and Control, 1971, 19(5): 417.

    Article  MathSciNet  Google Scholar 

  11. Lee, R.C.T., Chang, C.L., Fuzzy logic and the resolution principle,J. Assoc. Comput. Mach. 1972, 19(1): 109.

    MATH  MathSciNet  Google Scholar 

  12. Liu, X.H., Deng, A.S., Boolean operator fuzzy logic,Science in China, Ser. A, 1994, 37(8): 1009.

    MATH  MathSciNet  Google Scholar 

  13. Deng, A.S., Liu, X.H., Reasoning formalism in Boolean operator fuzzy logic,Science in China, Ser. A, 1995, 38(10): 1261.

    MATH  MathSciNet  Google Scholar 

  14. Deng, A. S., Generalized completeness of resolution in Boolean operator fuzzy logic,Chinese Science Bulletin, 1995, 40 (24): 2092.

    MATH  MathSciNet  Google Scholar 

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Project supported by the National Natural Science Foundation of China (Grant No. 69703010).

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Deng, A., Zhang, L. Limitations of quantitative operator fuzzy logic. Sci. China Ser. E-Technol. Sci. 41, 608–616 (1998). https://doi.org/10.1007/BF02917044

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  • DOI: https://doi.org/10.1007/BF02917044

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