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Tytuł artykułu

A probabilistic approach to fuzzy and crisp interval ordering

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper presents a new method of crisp and fuzzy interval comparison (ordering). The method is based on the probabilistic approach and the representation of fuzzy numbers as ordered a-level sets. It allows all the cases of interval location and overlapping to be taken into account, including the ordering of intervals and real numbers. Additionally, the method implicitly allows the widths of intervals to be used in ordering procedures. It should be noted that the probabilistic approach was employed only to infer the set of formulas needed to estimate quantitatively the degree to which one interval is less than or equal to another interval. However, the measure of this value may be treated as probability. Some simple examples are also presented to illustrate the technique's practical efficiency.
Rocznik
Strony
147--156
Opis fizyczny
Bibliogr. 19 poz., rys., tab.
Twórcy
  • Institute of Computer and Information Sciences, Technical University of Częstochowa, Dąbrowskiego 73, 42-201 Częstochowa, Poland
autor
  • Institute of Computer and Information Sciences, Technical University of Częstochowa, Dąbrowskiego 73, 42-201 Częstochowa, Poland
Bibliografia
  • [1] Baas S M and Kwakernaak H 1977 Automatica (AAAI-86)1347
  • [2] Ishihashi H and Tanaka M 1990 European J. Operational Research48219
  • [3] Chanas S and Kuchta D 1996 European J. Operational Research94594
  • [4] Moore R E rval Analysis – Englewood Cliffs, Prentice-Hall
  • [5] Kulpa Z 1997 Machine Graphics and Vision6(1) 5
  • [6] Heilpern S 1997 Fuzzy Sets and Systems91259
  • [7] Dubois D and Prade H 1983 Inform. Sci.30183
  • [8] Yager R R 1981 Inform. Sci.24143
  • [9] Yager R R 1999 Int. J. Intelligent Systems141249
  • [10] Rommelfanger H 1994 Fuzzy Support-Systems, Springer Verlag
  • [11] Yager R R and Detyniecki M 2000 Int. J. Uncertainty, Fuzziness and Knowledge-basedSystems8573
  • [12] Bortolan G and Degani R 1985 Fuzzy Sets and Systems151
  • [13] Facchinetti G, Ricci R G and Muzzioli S 1998 Int. J. Intelligent Systems13613
  • [14] Wang X and Kerre E E 2001 Fuzzy Sets and Systems112375;ibid.387
  • [15] Sevastianov P, Róg P and Karczewski K 2002 Computer Science2(2) 45
  • [16] Luus R and Jaakola T 1973 AIChE J.19760
  • [17] Sevastianov P and Venberg A 1998 Energetic MinskN 366 (in Russian)
  • [18] Sevastianov P and Valkovsky V 1999 Information Technologies MoscowN 623 (in Russian)
  • [19] Sevastianov P and Valkovsky V 1999 Resources. Information. Supply. Competition MoscowN 2–379 (in Russian)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT3-0009-0039
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