[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Skip to main content

Part of the book series: Springer Handbooks ((SHB))

Abstract

Many different kinds of sets have been defined within the framework of fuzzy sets . This paper focusses on those fuzzy set extensions that address the difficulties that experts find in order to build the membership values. In particular, we analyze type-2 fuzzy sets , interval-valued fuzzy sets , Atanassov’s intuitionistic fuzzy sets , or bipolar sets of type-2 and Atanassov’s interval-valued fuzzy sets. After stating a general approach to these extensions, we remark some structural problems in the extension problem and stress some applications for which the results obtained with extensions are better than those obtained with Zadeh’s fuzzy sets.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
GBP 19.95
Price includes VAT (United Kingdom)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
GBP 223.50
Price includes VAT (United Kingdom)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
GBP 279.99
Price includes VAT (United Kingdom)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Abbreviations

FDT:

fuzzy decision tree

FRBCS:

fuzzy rule-based classification systems

FURIA:

unordered fuzzy rule induction algorithm

GAGRAD:

genetic algorithm gradient

IF:

intuitionistic fuzzy

References

  1. L.A. Zadeh: Fuzzy sets, Inf. Control 8, 338–353 (1965)

    Article  MathSciNet  MATH  Google Scholar 

  2. J.A. Goguen: L-fuzzy sets, J. Math. Anal. Appl. 18, 145–174 (1967)

    Article  MathSciNet  MATH  Google Scholar 

  3. J.T. Cacioppo, W.L. Gardner, C.G. Berntson: Beyond bipolar conceptualizations and measures: The case of attitudes and evaluative space, Pers. Soc. Psychol. Rev. 1, 3–25 (1997)

    Article  Google Scholar 

  4. R. Goldblatt: Topoi: The Categorial Analysis of Logic (North-Holland, Amsterdam 1979)

    MATH  Google Scholar 

  5. S.M. Lane, I. Moerfijk: Sheaves in Geometry and Logic (Springer, New York 1992)

    Book  Google Scholar 

  6. G. Takeuti, S. Titani: Intuitionistic fuzzy logic and intuitionistic fuzzy set theory, J. Symb. Log. 49, 851–866 (1984)

    Article  MathSciNet  MATH  Google Scholar 

  7. D. Dubois, S. Gottwald, P. Hajek, J. Kacprzyk, H. Prade: Terminological difficulties in fuzzy set theory — The case of intuitionistic fuzzy sets, Fuzzy Sets Syst. 156(3), 485–491 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  8. G. Birkhoff: Lattice Theory (American Mathematical Society, Providence 1973)

    MATH  Google Scholar 

  9. R. Willmott: Mean Measures in Fuzzy Power-Set Theory, Report No. FRP-6 (Dep. Math., Univ. Essex , Colchester 1979)

    Google Scholar 

  10. W. Bandler, L. Kohout: Fuzzy power sets, fuzzy implication operators, Fuzzy Sets Syst. 4, 13–30 (1980)

    Article  MathSciNet  MATH  Google Scholar 

  11. B. De Baets, E.E. Kerre, M. Gupta: The fundamentals of fuzzy mathematical morphology – part 1: Basic concepts, Int. J. Gen. Syst. 23(2), 155–171 (1995)

    Article  MATH  Google Scholar 

  12. L.K. Huang, M.J. Wang: Image thresholding by minimizing the measure of fuzziness, Pattern Recognit. 29(1), 41–51 (1995)

    Article  Google Scholar 

  13. H. Bustince, J. Montero, E. Barrenechea, M. Pagola: Semiautoduality in a restricted family of aggregation operators, Fuzzy Sets Syst. 158(12), 1360–1377 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  14. T. Calvo, A. Kolesárová, M. Komorníková, R. Mesiar: Aggregation operators: Properties, classes and construction methods. In: Aggregation Operators New Trends and Applications, ed. by T. Calvo, G. Mayor, R. Mesiar (Physica, Heidelberg 2002) pp. 3–104

    Chapter  Google Scholar 

  15. J. Fodor, M. Roubens: Fuzzy preference modelling and multicriteria decision support, Theory and Decision Library (Kluwer, Dordrecht 1994)

    Book  MATH  Google Scholar 

  16. E.P. Klement, R. Mesiar, E. Pap: Triangular norms, trends in logic, Studia Logica Library (Kluwer, Dordrecht 2000)

    Book  MATH  Google Scholar 

  17. L.A. Zadeh: Quantitative fuzzy semantics, Inf. Sci. 3, 159–176 (1971)

    Article  MathSciNet  MATH  Google Scholar 

  18. E.E. Kerre: A first view on the alternatives of fuzzy sets theory. In: Computational Intelligence in Theory and Practice, ed. by B. Reusch, K.-H. Temme (Physica, Heidelberg 2001) pp. 55–72

    Chapter  Google Scholar 

  19. M. Mizumoto, K. Tanaka: Some properties of fuzzy sets of type 2, Inf. Control 31, 312–340 (1976)

    Article  MathSciNet  MATH  Google Scholar 

  20. D. Dubois, H. Prade: Operations in a fuzzy-valued logic, Inf. Control 43(2), 224–254 (1979)

    Article  MathSciNet  MATH  Google Scholar 

  21. J. Harding, C. Walker, E. Walker: The variety generated by the truth value algebra of type-2 fuzzy sets, Fuzzy Sets Syst. 161, 735–749 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  22. J.M. Mendel, R.I. John: Type-2 fuzzy sets made simple, IEEE Trans. Fuzzy Syst. 10, 117–127 (2002)

    Article  Google Scholar 

  23. J. Aisbett, J.T. Rickard, D.G. Morgenthaler: Type-2 fuzzy sets as functions on spaces, IEEE Trans. Fuzzy Syst. 18(4), 841–844 (2010)

    Article  Google Scholar 

  24. G. Deschrijver, E.E. Kerre: On the position of intuitionistic fuzzy set theory in the framework of theories modelling imprecision, Inf. Sci. 177, 1860–1866 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  25. G. Deschrijver, E.E. Kerre: On the relationship between some extensions of fuzzy set theory, Fuzzy Sets Syst. 133, 227–235 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  26. D. Dubois, H. Prade: Fuzzy Sets and Systems: Theory and Applications (Academic, New York 1980)

    MATH  Google Scholar 

  27. G.J. Klir, B. Yuan: Fuzzy Sets and Fuzzy Logic: Theory and Applications (Prentice-Hall, New Jersey 1995)

    MATH  Google Scholar 

  28. J.M. Mendel: Type-2 fuzzy sets for computing with words, IEEE Int. Conf. Granul. Comput., Atlanta (2006), GA 8-8

    Google Scholar 

  29. J.M. Mendel: Computing with words and its relationships with fuzzistics, Inf. Sci. 177(4), 988–1006 (2007)

    Article  MathSciNet  Google Scholar 

  30. J.M. Mendel: Historical reflections on perceptual computing, Proc. 8th Int. FLINS Conf. (FLINS'08) (World Scientific, Singapore 2008) pp. 181–187

    Google Scholar 

  31. J.M. Mendel: Computing with words: Zadeh, Turing, Popper and Occam, IEEE Comput. Intell. Mag. 2, 10–17 (2007)

    Article  Google Scholar 

  32. H. Hagras: Type-2 FLCs: A new generation of fuzzy controllers, IEEE Comput. Intell. Mag. 2, 30–43 (2007)

    Article  Google Scholar 

  33. H. Hagras: A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots, IEEE Trans. Fuzzy Syst. 12, 524–539 (2004)

    Article  Google Scholar 

  34. R. Sepulveda, O. Castillo, P. Melin, A. Rodriguez-Diaz, O. Montiel: Experimental study of intelligent controllers under uncertainty using type-1 and type-2 fuzzy logic, Inf. Sci. 177, 2023–2048 (2007)

    Article  Google Scholar 

  35. X.S. Xia, Q.L. Liang: Crosslayer design for mobile ad hoc networks using interval type-2 fuzzy logic systems, Int. J. Uncertain. Fuzziness Knowl. Syst. 16(3), 391–408 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  36. C.H. Wang, C.S. Cheng, T.T. Lee: Dynamical optimal training for interval type-2 fuzzy neural network (T2FNN), IEEE Trans. Syst. Man Cybern. B 34(3), 14621477 (2004)

    Google Scholar 

  37. R. Sambuc: Fonction Φ-Flous, Application a l'aide au Diagnostic en Pathologie Thyroidienne, These de Doctorat en Medicine (Univ. Marseille, Marseille 1975)

    Google Scholar 

  38. K.U. Jahn: Intervall-wertige Mengen, Math. Nachr. 68, 115–132 (1975)

    Article  MathSciNet  MATH  Google Scholar 

  39. I. Grattan-Guinness: Fuzzy membership mapped onto interval and many-valued quantities, Z. Math. Log. Grundl. Math. 22, 149–160 (1976)

    Article  MathSciNet  MATH  Google Scholar 

  40. A. Dziech, M.B. Gorzalczany: Decision making in signal transmission problems with interval-valued fuzzy sets, Fuzzy Sets Syst. 23(2), 191–203 (1987)

    Article  MathSciNet  Google Scholar 

  41. M.B. Gorzalczany: A method of inference in approximate reasoning based on interval-valued fuzzy sets, Fuzzy Sets Syst. 21, 1–17 (1987)

    Article  MathSciNet  MATH  Google Scholar 

  42. M.B. Gorzalczany: An interval-valued fuzzy inference method. Some basic properties, Fuzzy Sets Syst. 31(2), 243–251 (1989)

    Article  MathSciNet  Google Scholar 

  43. I.B. Türksen: Interval valued fuzzy sets based on normal forms, Fuzzy Sets Syst. 20(2), 191–210 (1986)

    Article  MathSciNet  MATH  Google Scholar 

  44. I.B. Türksen, Z. Zhong: An approximate analogical reasoning schema based on similarity measures and interval-valued fuzzy sets, Fuzzy Sets Syst. 34, 323–346 (1990)

    Article  Google Scholar 

  45. I.B. Türksen, D.D. Yao: Representation of connectives in fuzzy reasoning: The view through normal forms, IEEE Trans. Syst. Man Cybern. 14, 191–210 (1984)

    MATH  Google Scholar 

  46. J.L. Deng: Introduction to grey system theory, J. Grey Syst. 1, 1–24 (1989)

    MathSciNet  MATH  Google Scholar 

  47. H. Bustince: Indicator of inclusion grade for interval-valued fuzzy sets. Application to approximate reasoning based on interval-valued fuzzy sets, Int. J. Approx. Reason. 23(3), 137–209 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  48. G. Deschrijver: The Archimedean property for t-norms in interval-valued fuzzy set theory, Fuzzy Sets Syst. 157(17), 2311–2327 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  49. G. Deschrijver, C. Cornelis, E.E. Kerre: On the representation of intuitionistic fuzzy t-norms and t-conorms, IEEE Trans. Fuzzy Syst. 12(1), 45–61 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  50. Z. Xu, R.R. Yager: Some geometric aggregation operators based on intuitionistic fuzzy sets, Int. J. Gen. Syst. 35, 417–433 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  51. H. Bustince, J. Fernandez, A. Kolesárová, M. Mesiar: Generation of linear orders for intervals by means of aggregation functions, Fuzzy Sets Syst. 220, 69–77 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  52. J. Montero, D. Gomez, H. Bustince: On the relevance of some families of fuzzy sets, Fuzzy Sets Syst. 158(22), 2429–2442 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  53. H. Bustince, F. Herrera, J. Montero: Fuzzy Sets and Their Extensions: Representation Aggregation and Models (Springer, Berlin 2007)

    MATH  Google Scholar 

  54. W. Pedrycz: Shadowed sets: Representing and processing fuzzy sets, IEEE Trans. Syst. Man Cybern. B 28, 103–109 (1998)

    Article  Google Scholar 

  55. W. Pedrycz, G. Vukovich: Investigating a relevance off uzzy mappings, IEEE Trans. Syst. Man Cybern. B 30, 249–262 (2000)

    Article  Google Scholar 

  56. W. Pedrycz, G. Vukovich: Granular computing with shadowed sets, Int. J. Intell. Syst. 17, 173–197 (2002)

    Article  MATH  Google Scholar 

  57. J.M. Mendel: Advances in type-2 fuzzy sets and systems, Inf. Sci. 177, 84–110 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  58. H. Bustince, J. Montero, M. Pagola, E. Barrenechea, D. Gomez: A survey of interval-valued fuzzy sets. In: Handbook of Granular Computing, ed. by W. Pedrycz (Wiley, New York 2008)

    Google Scholar 

  59. P. Burillo, H. Bustince: Entropy on intuitionistic fuzzy sets and on interval-valued fuzzy sets, Fuzzy Sets Syst. 78, 305–316 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  60. A. Jurio, M. Pagola, D. Paternain, C. Lopez-Molina, P. Melo-Pinto: Interval-valued restricted equivalence functions applied on clustering techniques, Proc. Int. Fuzzy Syst. Assoc. World Congr. Eur. Soc. Fuzzy Log. Technol. Conf. (2009) pp. 831–836

    Google Scholar 

  61. E. Szmidt, J. Kacprzyk: Entropy for intuitionistic fuzzy sets, Fuzzy Sets Syst. 118(3), 467–477 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  62. H. Rezaei, M. Mukaidono: New similarity measures of intuitionistic fuzzy sets, J. Adv. Comput. Intell. Inf. 11(2), 202–209 (2007)

    Google Scholar 

  63. H. Bustince, M. Pagola, E. Barrenechea, J. Fernandez, P. Melo-Pinto, P. Couto, H.R. Tizhoosh, J. Montero: Ignorance functions. An application to the calculation of the threshold in prostate ultrasound images, Fuzzy Sets Syst. 161(1), 20–36 (2010)

    Article  MathSciNet  Google Scholar 

  64. D. Wu: Approaches for reducing the computational cost of interval type-2 fuzzy logic systems: Overview and comparisons, IEEE Trans. Fuzzy Syst. 21(1), 80–99 (2013)

    Article  Google Scholar 

  65. H. Bustince, M. Galar, B. Bedregal, A. Kolesárová, R. Mesiar: A new approach to interval-valued Choquet integrals and the problem of ordering in interval-valued fuzzy set applications, IEEE Trans. Fuzzy Syst. 21(6), 1150–1162 (2013)

    Article  Google Scholar 

  66. J. Sanz, H. Bustince, F. Herrera: Improving the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets and genetic amplitude tuning, Inf. Sci. 180(19), 3674–3685 (2010)

    Article  Google Scholar 

  67. J. Sanz, A. Fernandez, H. Bustince, F. Herrera: A genetic tuning to improve the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets: Degree of ignorance and lateral position, Int. J. Approx. Reason. 52(6), 751–766 (2011)

    Article  Google Scholar 

  68. J. Sanz, A. Fernandez, H. Bustince, F. Herrera: IIVFDT: Ignorance functions based interval-valued fuzzy decision tree with genetic tuning, Int. J. Uncertain. Fuzziness Knowl.-Based Syst. 20(Suppl. 2), 1–30 (2012)

    Article  MathSciNet  Google Scholar 

  69. J. Sanz, A. Fernandez, H. Bustince, F. Herrera: IVTURS: A linguistic fuzzy rule-based classification system based on a new interval-valued fuzzy reasoning method with tuning and rule selection, IEEE Trans. Fuzzy Syst. 21(3), 399–411 (2013)

    Article  Google Scholar 

  70. Z. Chi, H. Yan, T. Pham: Fuzzy Algorithms with Applications to Image Processing and Pattern Recognition (World Scientific, Singapore 1996)

    MATH  Google Scholar 

  71. H. Ishibuchi, T. Yamamoto, T. Nakashima: Hybridization of fuzzy GBML approaches for pattern classification problems, IEEE Trans. Syst. Man Cybern. B 35(2), 359–365 (2005)

    Article  Google Scholar 

  72. J. Dombi, Z. Gera: Rule based fuzzy classification using squashing functions, J. Intell. Fuzzy Syst. 19(1), 3–8 (2008)

    MATH  Google Scholar 

  73. R. Alcalá, J. Alacalá-Fdez, F. Herrera: A proposal for the genetic lateral tuning of linguistic fuzzy systems and its interaction with rule selection, IEEE Trans. Fuzzy Syst. 15(4), 616–635 (2007)

    Article  Google Scholar 

  74. R. Alcalá, J. Alacalá-Fdez, M. Graco, F. Herrera: Rule base reduction and genetic tuning of fuzzy systems based on the linguistic 3-tuples representation, Soft Comput. 11(5), 401–419 (2007)

    Article  Google Scholar 

  75. J. Quinlan: C4.5: Programs for Machine Learning (Morgan Kaufmann, San Mateo 1993)

    Google Scholar 

  76. C.Z. Janikow: Fuzzy decision trees: Issues and methods, IEEE Trans. Syst. Man Cybern. B 28(1), 1–14 (1998)

    Article  Google Scholar 

  77. J. Alacalá-Fdez, R. Alcalá, F. Herrera: A fuzzy association rule-based classification model for high-dimensional problems with genetic rule selection and lateral tuning, IEEE Trans. Fuzzy Syst. 19(5), 857–872 (2011)

    Article  Google Scholar 

  78. J. Hühn, E. Hüllermeier: FURIA: An algorithm for unordered fuzzy rule induction, Data Min. Knowl. Discov. 19(3), 293–319 (2009)

    Article  MathSciNet  Google Scholar 

  79. E. Barrenechea, H. Bustince, B. De Baets, C. Lopez-Molina: Construction of interval-valued fuzzy relations with application to the generation of fuzzy edge images, IEEE Trans. Fuzzy Syst. 19(5), 819–830 (2011)

    Article  Google Scholar 

  80. H. Bustince, P.M. Barrenechea, J. Fernandez, J. Sanz: “Image thresholding using type II fuzzy sets.” Importance of this method, Pattern Recognit. 43(9), 3188–3192 (2010)

    Article  MATH  Google Scholar 

  81. H. Bustince, E. Barrenechea, M. Pagola, J. Fernandez: Interval-valued fuzzy sets constructed from matrices: Application to edge detection, Fuzzy Sets Syst. 60(13), 1819–1840 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  82. M. Galar, F. Fernandez, G. Beliakov, H. Bustince: Interval-valued fuzzy sets applied to stereo matching of color images, IEEE Trans. Image Process. 20, 1949–1961 (2011)

    Article  MathSciNet  Google Scholar 

  83. M. Pagola, C. Lopez-Molina, J. Fernandez, E. Barrenechea, H. Bustince: Interval type-2 fuzzy sets constructed from several membership functions. Application to the fuzzy thresholding algorithm, IEEE Trans. Fuzzy Syst. 21(2), 230–244 (2013)

    Article  Google Scholar 

  84. H.R. Tizhoosh: Image thresholding using type-2 fuzzy sets, Pattern Recognit. 38, 2363–2372 (2005)

    Article  MATH  Google Scholar 

  85. M.E. Yuksel, M. Borlu: Accurate segmentation of dermoscopic images by image thresholding based on type-2 fuzzy logic, IEEE Trans. Fuzzy Syst. 17(4), 976–982 (2009)

    Article  Google Scholar 

  86. C. Shyi-Ming, W. Hui-Yu: Evaluating students answer scripts based on interval-valued fuzzy grade sheets, Expert Syst. Appl. 36(6), 9839–9846 (2009)

    Article  Google Scholar 

  87. F. Liu, H. Geng, Y.-Q. Zhang: Interactive fuzzy interval reasoning for smart web shopping, Appl. Soft Comput. 5(4), 433–439 (2005)

    Article  Google Scholar 

  88. C. Byung-In, C.-H.R. Frank: Interval type-2 fuzzy membership function generation methods for pattern recognition, Inf. Sci. 179(13), 2102–2122 (2009)

    Article  MATH  Google Scholar 

  89. H.M. Choi, G.S. Min, J.Y. Ahn: A medical diagnosis based on interval-valued fuzzy sets, Biomed. Eng. Appl. Basis Commun. 24(4), 349–354 (2012)

    Article  Google Scholar 

  90. J.M. Mendel, H. Wu: Type-2 fuzzistics for symmetric interval type-2 fuzzy sets: Part 1: Forward problems, IEEE Trans. Fuzzy Syst. 14(6), 781–792 (2006)

    Article  Google Scholar 

  91. D. Wu, J.M. Mendel: A vector similarity measure for linguistic approximation: Interval type-2 and type-1 fuzzy sets, Inf. Sci. 178(2), 381–402 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  92. A. Jurio, H. Bustince, M. Pagola, A. Pradera, R.R. Yager: Some properties of overlap and grouping functions and their application to image thresholding, Fuzzy Sets Syst. 229, 69–90 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  93. K.T. Atanassov: Intuitionistic fuzzy sets, VII ITKRs Session, Central Sci.-Tech. Libr. Bulg. Acad. Sci., Sofia (1983) pp. 1684–1697, (in Bulgarian)

    Google Scholar 

  94. K.T. Atanassov: Intuitionistic fuzzy sets, Fuzzy Sets Syst. 20, 87–96 (1986)

    Article  MathSciNet  MATH  Google Scholar 

  95. W.L. Gau, D.J. Buehrer: Vague sets, IEEE Trans. Syst. Man Cybern. 23(2), 610–614 (1993)

    Article  MATH  Google Scholar 

  96. H. Bustince, P. Burillo: Vague sets are intuitionistic fuzzy sets, Fuzzy Sets Syst. 79(3), 403–405 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  97. H. Bustince, E. Barrenechea, P. Pagola: Generation of interval-valued fuzzy and Atanassov's intuitionistic fuzzy connectives from fuzzy connectives and from $K_{{\alpha}}$ operators: Laws for conjunctions and disjunctions, amplitude, Int. J. Intell. Syst. 32(6), 680–714 (2008)

    Article  MATH  Google Scholar 

  98. K.T. Atanassov, G. Gargov: Interval valued intuitionistic fuzzy sets, Fuzzy Sets Syst. 31(3), 343–349 (1989)

    Article  MathSciNet  MATH  Google Scholar 

  99. J. Ye: Fuzzy decision-making method based on the weighted correlation coefficient under intuitionistic fuzzy environment, Eur. J. Oper. Res. 205(1), 202–204 (2010)

    Article  MATH  Google Scholar 

  100. F. Herrera, E. Herrera-Viedma: Linguistic decision analysis: Steps for solving decision problems under linguistic information, Fuzzy Sets Syst. 115, 67–82 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  101. L. Baccour, A.M. Alimi, R.I. John: Similarity measures for intuitionistic fuzzy sets: State of the art, J. Intell. Fuzzy Syst. 24(1), 37–49 (2013)

    MathSciNet  MATH  Google Scholar 

  102. E. Szmidt, J. Kacprzyk, P. Bujnowski: Measuring the amount of knowledge for Atanassovs intuitionistic fuzzy sets, Lect. Notes Comput. Sci. 6857, 17–24 (2011)

    Article  MATH  Google Scholar 

  103. N.R. Pal, H. Bustince, M. Pagola, U.K. Mukherjee, D.P. Goswami, G. Beliakov: Uncertainties with Atanassov's intuitionistic fuzzy sets: fuzziness and lack of knowledge, Inf. Sci. 228, 61–74 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  104. U. Dudziak, B. Pekala: Equivalent bipolar fuzzy relations, Fuzzy Sets Syst. 161(2), 234–253 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  105. Z. Xu: Approaches to multiple attribute group decision making based on intuitionistic fuzzy power aggregation operators, Knowl. Syst. 24(6), 749–760 (2011)

    Article  Google Scholar 

  106. Z. Xu, H. Hu: Projection models for intuitionistic fuzzy multiple attribute decision making, Int. J. Inf. Technol. Decis. Mak. 9(2), 257–280 (2010)

    Article  MATH  Google Scholar 

  107. Z. Xu: Priority weights derived from intuitionistic multiplicative preference relations in decision making, IEEE Trans. Fuzzy Syst. 21(4), 642–654 (2013)

    Article  Google Scholar 

  108. X. Zhang, Z. Xu: A new method for ranking intuitionistic fuzzy values and its application in multi-attribute decision making, Fuzzy Optim. Decis. Mak. 11(2), 135–146 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  109. T. Chen: Multi-criteria decision-making methods with optimism and pessimism based on Atanassov's intuitionistic fuzzy sets, Int. J. Syst. Sci. 43(5), 920–938 (2012)

    Article  MATH  Google Scholar 

  110. S.K. Biswas, A.R. Roy: An application of intuitionistic fuzzy sets in medical diagnosis, Fuzzy Sets Syst. 117, 209–213 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  111. I. Bloch: Lattices of fuzzy sets and bipolar fuzzy sets, and mathematical morphology, Inf. Sci. 181(10), 2002–2015 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  112. P. Melo-Pinto, P. Couto, H. Bustince, E. Barrenechea, M. Pagola, F. Fernandez: Image segmentation using Atanassov's intuitionistic fuzzy sets, Expert Syst. Appl. 40(1), 15–26 (2013)

    Article  MATH  Google Scholar 

  113. P. Couto, A. Jurio, A. Varejao, M. Pagola, H. Bustince, P. Melo-Pinto: An IVFS-based image segmentation methodology for rat gait analysis, Soft Comput. 15(10), 1937–1944 (2011)

    Article  Google Scholar 

  114. K.T. Atanassov: Answer to D. Dubois, S. Gottwald, P. Hajek, J. Kacprzyk and H. Prade's paper Terminological difficulties in fuzzy set theory – The case of Intuitionistic fuzzy sets, Fuzzy Sets Syst. 156(3), 496–499 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  115. D. Dubois, H. Prade: An introduction to bipolar representations of information and preference, Int. J. Intell. Syst. 23, 866–877 (2008)

    Article  MATH  Google Scholar 

  116. D. Dubois, H. Prade: An overview of the asymmetric bipolar representation of positive and negative information in possibility theory, Fuzzy Sets Syst. 160(10), 1355–1366 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  117. W.R. Zhang: NPN fuzzy sets and NPN qualitative algebra: a computational framework for bipolar cognitive modeling and multiagent decision analysis, IEEE Trans. Syst. Man Cybern. B 26(4), 561–574 (1996)

    Article  Google Scholar 

  118. W.R. Zhang: Bipolar logic and bipolar fuzzy partial orderings for clustering and coordination, Proc. 6th Joint Conf. Inf. Sci. (2002) pp. 85–88

    Google Scholar 

  119. P. Grzegorzewski: On some basic concepts in probability of IF-events, Inf. Sci. 232, 411–418 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  120. H. Bustince, P. Burillo: Correlation of interval-valued intuitionistic fuzzy sets, Fuzzy Sets Syst. 74(2), 237–244 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  121. J. Wu, F. Chiclana: Non-dominance and attitudinal prioritisation methods for intuitionistic and interval-valued intuitionistic fuzzy preference relations, Expert Syst. Appl. 39(18), 13409–13416 (2012)

    Article  Google Scholar 

  122. Z. Xu, Q. Chen: A multi-criteria decision making procedure based on interval-valued intuitionistic fuzzy bonferroni means, J. Syst. Sci. Syst. Eng. 20(2), 217–228 (2011)

    Article  Google Scholar 

  123. J. Ye: Multicriteria decision-making method using the Dice similarity measure based on the reduct intuitionistic fuzzy sets of interval-valued intuitionistic fuzzy sets, Appl. Math. Model. 36(9), 4466–4472 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  124. A. Aygunoglu, B.P. Varol, V. Cetkin, H. Aygun: Interval-valued intuitionistic fuzzy subgroups based on interval-valued double t-norm, Neural Comput. Appl. 21(1), S207–S214 (2012)

    Article  Google Scholar 

  125. M. Fanyong, Z. Qiang, C. Hao: Approaches to multiple-criteria group decision making based on interval-valued intuitionistic fuzzy Choquet integral with respect to the generalized lambda-Shapley index, Knowl. Syst. 37, 237–249 (2013)

    Article  Google Scholar 

  126. W. Wang, X. Liu, Y. Qin: Interval-valued intuitionistic fuzzy aggregation operators 14, J. Syst. Eng. Electron. 23(4), 574–580 (2012)

    Article  Google Scholar 

  127. K. Hirota: Concepts of probabilistic sets, Fuzzy Sets Syst. 5, 31–46 (1981)

    Article  MathSciNet  MATH  Google Scholar 

  128. R.R. Yager: On the theory of bags, Int. J. Gen. Syst. 13, 23–37 (1986)

    Article  MathSciNet  Google Scholar 

  129. S. Miyamoto: Multisets and fuzzy multisets. In: Soft Computing and Human-Centered Machines, ed. by Z.-Q. Liu, S. Miyamoto (Springer, Berlin 2000) pp. 9–33

    Chapter  Google Scholar 

  130. Y. Shang, X. Yuan, E.S. Lee: The n-dimensional fuzzy sets and Zadeh fuzzy sets based on the finite valued fuzzy sets, Comput. Math. Appl. 60, 442–463 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  131. B. Bedregal, G. Beliakov, H. Bustince, T. Calvo, R. Mesiar, D. Paternain: A class of fuzzy multisets with a fixed number of memberships, Inf. Sci. 189, 1–17 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  132. A. Amo, J. Montero, G. Biging, V. Cutello: Fuzzy classification systems, Eur. J. Oper. Res. 156, 459–507 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  133. J. Montero: Arrow`s theorem under fuzzy rationality, Behav. Sci. 32, 267–273 (1987)

    Article  Google Scholar 

  134. A. Mesiarová, J. Lazaro: Bipolar Aggregation operators, Proc. AGOP2003, Al-calá de Henares (2003) pp. 119–123

    Google Scholar 

  135. A. Mesiarová-Zemánková, R. Mesiar, K. Ahmad: The balancing Choquet integral, Fuzzy Sets Syst. 161(17), 2243–2255 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  136. A. Mesiarová-Zemánková, K. Ahmad: Multi-polar Choquet integral, Fuzzy Sets Syst. 220, 1–20 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  137. W.R. Zhang, L. Zhang: YinYang bipolar logic and bipolar fuzzy logic, Inf. Sci. 165(3/4), 265–287 (2004)

    Article  MATH  Google Scholar 

  138. W.R. Zhang: YinYang Bipolar T-norms and T-conorms as granular neurological operators, Proc. IEEE Int. Conf. Granul. Comput., Atlanta (2006) pp. 91–96

    Google Scholar 

  139. F. Smarandache: A unifying field in logics: Neutrosophic logic, Multiple-Valued Logic 8(3), 385–438 (2002)

    MathSciNet  MATH  Google Scholar 

  140. V. Torra: Hesitant fuzzy sets, Int. J. Intell. Syst. 25, 529539 (2010)

    MATH  Google Scholar 

  141. V. Torra, Y. Narukawa: On hesitant fuzzy sets and decision, Proc. Conf. Fuzzy Syst. (FUZZ IEEE) (2009) pp. 1378–1382

    Google Scholar 

  142. D. Molodtsov: Soft set theory. First results, Comput. Math. Appl. 37, 19–31 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  143. P.K. Maji, R. Biswas, R. Roy: Fuzzy soft sets, J. Fuzzy Math. 9(3), 589–602 (2001)

    MathSciNet  MATH  Google Scholar 

  144. Z. Pawlak: Rough sets, Int. J. Comput. Inf. Sci. 11, 341–356 (1982)

    Article  MathSciNet  MATH  Google Scholar 

  145. D. Dubois, H. Prade: Rough fuzzy-sets and fuzzy rough sets, Int. J. Gen. Syst. 17(3), 191–209 (1990)

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Humberto Bustince .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Bustince, H., Barrenechea, E., Fernández, J., Pagola, M., Montero, J. (2015). The Origin of Fuzzy Extensions. In: Kacprzyk, J., Pedrycz, W. (eds) Springer Handbook of Computational Intelligence. Springer Handbooks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43505-2_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-43505-2_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-43504-5

  • Online ISBN: 978-3-662-43505-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics