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Entropy and information energy arithmetic operations for fuzzy numbers

  • Hong, Dug-Hun (Department of Mathematics, Myongji University) ;
  • Kim, Kyung-Tae (Department of Electronics and Electrical Information Engineering, Kyungwon University)
  • Published : 2005.12.01

Abstract

There have been several tipical methods being used tomeasure the fuzziness (entropy) of fuzzy sets. Pedrycz is the original motivation of this paper. Recently, Wang and Chiu [FSS103(1999) 443-455] and Pedrycz [FSS 64(1994) 21-30] showed the relationship(addition, subtraction, multiplication) between the entropies of the resultant fuzzy number and the original fuzzy numbers of same type. In this paper, using Lebesgue-Stieltjes integral, we generalize results of Wang and Chiu [FSS 103(1999) 443-455] concerning entropy arithmetic operations without the condition of same types of fuzzy numbers. And using this results and trade-off relationship between information energy and entropy, we study more properties of information energy of fuzzy numbers.

Keywords

References

  1. Y. H. Chen and W. J. Wang, Fuzzy entropy management via scaling, elevation, and saturation, Fuzzy Sets and Systems 95(1998) 173-178 https://doi.org/10.1016/S0165-0114(96)00321-1
  2. A. De Luca and S. Termini, A definition of nonprobabilistic entropy in the setting of fuzzy sets theory, Inform. Control 20 (1972) 301-312 https://doi.org/10.1016/S0019-9958(72)90199-4
  3. D. Dumitrescu, Entropy of a fuzzy process, Fuzzy Sets and Systems 55(1993) 169-177 https://doi.org/10.1016/0165-0114(93)90129-6
  4. D. Dumitrescu, Entropy of fuzzy dynamical systems, Fuzzy Sets and Systems 70(1995) 45-47 https://doi.org/10.1016/0165-0114(94)00245-3
  5. D. Dumitrescu, A definition of an information energy in fuzzy sets theory, Studia Univ. Babes-bolyai Math. 22(1977) 57-59
  6. D. H. Hong and J. H. Kim, Some formulae to calculate the entropies of the image fuzzy sets, Uncertainty, Fuzziness and Knowledge-Based Systems 11(2003) 615-626 https://doi.org/10.1142/S0218488503002363
  7. A. Kaufmann, Introduction to the Theory of Fuzzy Subsets, Academic Press, New York, 1975
  8. G. J. Klir, B. Yuan, Fuzzy Sets and Fuzzy Logic Theory and Applications, Prentic-Hall PTR, Englewood Cliffs, NJ, 1995
  9. D. L. Mon, C.H. Cheng, J.C. Lin, Evaluating weapon system using fuzzy analytic hierarchy process based on entropy weight, Fuzzy Sets and Systems 62(1994) 127-134 https://doi.org/10.1016/0165-0114(94)90052-3
  10. W. Pedrycz, Why triangular membership function, Fuzzy Sets and Systems 64(1994) 21-30 https://doi.org/10.1016/0165-0114(94)90003-5
  11. C. E. Shannon and W. Weaver, The mathematical theory of communication (University of Illinois Press, Urbana, 1964)
  12. W. Wang and C. Chiu, The entropy change in extension principle, Fuzzy Sets and Systems 103(1999) 153-162 https://doi.org/10.1016/S0165-0114(97)00162-0
  13. W. Wang and C. Chiu, Entropy variation on the fuzzy numbers with arithmetic operations, Fuzzy Sets and Systems 103(1999) 443-455 https://doi.org/10.1016/S0165-0114(99)80001-3
  14. W. Wang and C. Chiu, Entropy and information energy for fuzzy sets, Fuzzy Sets and System 108(1999) 333-339 https://doi.org/10.1016/S0165-0114(97)00344-8
  15. R. L. Wheeden and A. Zygmund, Measure and Integration (Marcel Dekker Inc. New York and Basel, 1977)
  16. L. Xuecheng, Entropy, distance measure and similarity measure of fuzzy sets and their relations, Fuzzy Sets and Systems 52(1979) 305-318 https://doi.org/10.1016/0165-0114(92)90239-Z
  17. R. R. Yager, On the measure of fuzziness and negation, Part I: membership in unit interval, Internat. J. General Systems 5(1979) 221-229 https://doi.org/10.1080/03081077908547452
  18. C. Yu, Correlation of fuzzy numbers, Fuzzy Sets and Systems 55(1993) 303-307 https://doi.org/10.1016/0165-0114(93)90256-H