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Ranking of fuzzy numbers by a new metric

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Abstract

In this paper, a new approach for comparison among fuzzy numbers based on new metric distance (D TM) is proposed. All reasonable properties of ranking function are proved. At first, the distance on the interval numbers based on convex hall of endpoints is proposed. The existing distance measures for interval numbers, (Bardossy and Duckstein in Fuzzy rule-based modeling with applications to geophysical, biological and engineering systems. CRC press, Boca Raton, 1995; Diamond in Info Sci 46:141–157, 1988; Diamond and Korner in Comput Math Appl 33:15–32, 1997; Tran and Duckstein in Fuzzy Set Syst 130:331–341, 2002; Diamond and Tanaka Fuzzy regression analysis. In: Slowinski R (ed) Fuzzy sets in decision analysis, operations research and statistics. Kluwer, Boston, pp 349–387, 1998) do not satisfy the properties of a metric distance, while the proposed distance does. It is extended to fuzzy numbers and its properties are proved in detail. Finally, we compare the proposed definition with some of the known ones.

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References

  • Abbasbandy S, Asady B (2006) Ranking of fuzzy numbers by sign distance. Inf Sci 176:2405–2416

    Article  MATH  MathSciNet  Google Scholar 

  • Bardossy A, Duckstein L (1995) Fuzzy rule-based modeling with applications to geophysical, biological and engineering systems. CRC press, Boca Raton

    MATH  Google Scholar 

  • Bardossy A, Hagaman R, Duckstein L, Bogardi I (1992) Fuzzy least squares regression: theory and application. In: Kacprzyk J, Fedrizi M (eds) Fuzzy l. Omnitech Press, Warsaw and Physica-Verlag, Heidelberg, pp 181–193

  • Bortolan G, Degan R (2006) A review of some method for ranking fuzzy sets. Fuzzy Sets Syst 15:1–19

    Article  Google Scholar 

  • Caldas M, Jafari S (2005) θ-Compact fuzzy topological spaces. Chaos Solitons Fractals 25:229–232

    Google Scholar 

  • Chang SL, Zadeh LA (1972) On fuzzy mapping and control. IEEE Trans Syst Man Cybern 2:30–34

    MATH  MathSciNet  Google Scholar 

  • Cheng CH (1998) A new approach for ranking fuzzy numbers by distance method. Fuzzy Sets Syst 95:307–317

    Article  MATH  Google Scholar 

  • Li DF, Yang JB (2004) Fuzzy linear programming technique for multiattribute group decision making in fuzzy environments. Inf Sci 158:263–275

    Article  MATH  Google Scholar 

  • Diamond P (1998) Fuzzy least squares. Inf Sci 46:141–157

    Article  MathSciNet  Google Scholar 

  • Diamond P, Korner R (1997) Extended fuzzy linear models and least squares estimates. Comput Math Appl 33:15–32

    Article  MATH  MathSciNet  Google Scholar 

  • Diamond P, Tanaka H (1998) Fuzzy regression analysis. In: Slowinski R (ed) Fuzzy sets in decision analysis, operations research and statistics. Kluwer, Boston, pp 349–387

  • Dubois D, Prade H (1980) Fuzzy sets and systems: theory and applications. Academic Press, New York

    MATH  Google Scholar 

  • Elnaschie MS (2004) A review of E-infinity theory and the mass spectrum of high energy particle physics. Chaos Solitons Fractals 19:209–236

    Article  Google Scholar 

  • Elnaschie MS (2006a) Elementary number theory in superstrings, loop quantum mechanics, twistors and E-infinity high energy physics. Chaos Solitons Fractals 27:297–330

    Article  Google Scholar 

  • Elnaschie MS (2006b) Superstrings, entropy and the elementary particles content of the standard model. Chaos Solitons Fractals 29:48–54

    Article  Google Scholar 

  • Feng G, Chen G (2005) Adaptive control of discrete-time chaotic systems: a fuzzy control approach. Chaos Solitons Fractals 23:459–467

    Google Scholar 

  • Fortemps P, Roubens M (1996) Ranking and defuzzification methods based on area compaensation. Fuzzy Sets Syst 82:319–330

    Article  MATH  MathSciNet  Google Scholar 

  • Goetschel R, Vaxman W (1981) A pseudometric for fuzzy sets and certain related result. J Math Anal Appl 81:507–523

    Article  MATH  MathSciNet  Google Scholar 

  • Goetschel R, Vaxman W (1983) Topological properties of fuzzy numbers. Fuzzy Sets Syst 10:87–99

    Article  MATH  Google Scholar 

  • Huang H, Wu CH (2009) On the triangle inequalities in fuzzy metric spaces. Inf Sci (in press)

  • Jiang W, Guo-Dong Q, Bin D (2005) H variable universe adaptive fuzzy control for chaotic system. Chaos Solitons Fractals 24:1075–1086

    Article  MATH  MathSciNet  Google Scholar 

  • Ma M, Kandel A, Friedman M (2000a) A new approach for defuzzification. Fuzzy Sets Syst 111:351–356

    Article  MATH  MathSciNet  Google Scholar 

  • Ma M, Kandel A, Friedman M (2000b) Correction to “a new approach for defuzzification”. Fuzzy Sets Syst 128:133–134

    Article  MathSciNet  Google Scholar 

  • Modarres M, Nezhad SS (2001) Ranking fuzzy numbers by preference ratio. Fuzzy Sets Syst 118:429–439

    Article  MATH  Google Scholar 

  • Negoita CV, Ralescu DA (1975) Applications of fuzzy sets to systems analysis. Wiley, Now York

    MATH  Google Scholar 

  • Ekel PY, Fernando H, Schuffner Neto (2006) Algorithms of discrete optimization and their application to problems with fuzzy cofficients. Inf Sci 176:2846–2868

    Google Scholar 

  • Slavka B (2003) Alpa-bounds of fuzzy numbers, Inf Sci 152:237–266

    Google Scholar 

  • Tanaka Y, Mizuno Y, Kado T (2005) Chaotic dynamics in the Friedman equation. Chaos Solitons Fractals 24:407–422

    Google Scholar 

  • Tran L, Duckstein L (2002) Comparison of fuzzy numbers using a fuzzy distance measure. Fuzzy Sets Syst 130:331–341

    Article  MATH  MathSciNet  Google Scholar 

  • Wang X, Kree EE (2001) Reasonable properties for the ordering of fuzzy quantities I. Fuzzy Sets Syst 118:375–385

    Article  MATH  Google Scholar 

  • Xu R, Li C (2001) Multidimensional least-squares fitting with a fuzzy model. Fuzzy Sets Syst 119:215–223

    Article  MATH  Google Scholar 

  • Yang MS, Ko (1997) On cluster-wise fuzzy regression analysis. IEEE Transaction on Systems. Man Cybern B 27:1–13

  • Yao JS, Wu K (2000) Ranking fuzzy numbers based on decomposition principle and signed distance. Fuzzy Sets Syst 116:275–288

    Article  MATH  MathSciNet  Google Scholar 

  • Xu ZS, Chen J (2009) An iteractive metchod for fuzzy multiple attribute group decision making. Inf Sci (in press)

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Correspondence to Tofigh Allahviranloo.

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Allahviranloo, T., Firozja, M.A. Ranking of fuzzy numbers by a new metric. Soft Comput 14, 773–782 (2010). https://doi.org/10.1007/s00500-009-0464-7

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