Abstract
Dealing with vague or imprecise information has been always a challenging problem. Different tools have been proposed to manage that uncertainty. A new model based on hesitant fuzzy sets was presented to manage situations where experts hesitate among several values to assess alternatives, variables, etc. Hesitant fuzzy sets models quantitative settings, however, it could occur similar situations but in qualitative settings, where experts think of several possible linguistic values or richer expressions than a single linguistic term to assess alternatives, variables, etc. In this contribution the aim is to introduce the concept of Hesitant Fuzzy Linguistic Term Sets (HFLTS) that will provide a linguistic elicitation based on the fuzzy linguistic approach and the use of context-free grammars.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Atanassov, K.T.: Intuitionistic fuzzy sets. Fuzzy Sets and Systems 20, 87–96 (1986)
Bonissone, P.P.: A fuzzy sets based linguistic approach: theory and applications. In: Gupta, M.M., Sanchez, E. (eds.) Approximate Reasoning in Decision Analysis, pp. 99–111. North-Holland Publishing Company (1982)
Bordogna, G., Pasi, G.: A fuzzy linguistic approach generalizing boolean information retrieval: A model and its evaluation. Journal of the American Society for Information Science 44, 70–82 (1993)
Dong, Y., Xu, Y., Yu, S.: Computing the numerical scale of the linguistic term set for the 2-tuple fuzzy linguistic representation model. IEEE Transactions on Fuzzy Systems 17(6), 1366–1378 (2009)
Dubois, D., Prade, H.: Fuzzy Sets and Systems: Theory and Applications. Kluwer Academic, New York (1980)
Herrera, F., Martínez, L.: A 2-tuple fuzzy linguistic representation model for computing with words. IEEE Transactions on Fuzzy Systems 8(6), 746–752 (2000)
Ishibuchi, H., Tanaka, H.: Theory and methodology: Multiobjective programming in optimization of the interval objective function. European Journal of Operational Research 48, 219–225 (1990)
Kundu, S.: Min-transitivity of fuzzy leftness relationship and its application to decision making. Fuzzy Sets and Systems 86, 357–367 (1997)
Li, D.F.: Multiattribute group decision making method using extended linguistic variables. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 17(6), 793–806 (2009)
Liu, J., Martínez, L., Wang, H., Rodríguez, R.M., Novozhilov, V.: Computing with words in risk assessment. International Journal of Computational Intelligence Systems 3(4), 396–419 (2010)
Martínez, L.: Sensory evaluation based on linguistic decision analysis. International Journal of Approximate Reasoning 44(2), 148–164 (2007)
Martínez, L., Liu, J., Yang, J.B.: A fuzzy model for design evaluation based on multiple criteria analysis in engineering systems. International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems 14(3), 317–336 (2006)
Martínez, L., Pérez, L.G., Barranco, M.: A multi-granular linguistic based-content recommendation model. International Journal of Intelligent Systems 22(5), 419–434 (2007)
Martínez, L., Ruan, D., Herrera, F.: Computing with words in decision support systems: An overview on models and applications. International Journal of Computational Intelligence Systems 3(4), 382–395 (2010)
Mendel, J.M.: An architecture for making judgement using computing with words. International Journal of Applied Mathematics and Computer Sciences 12(3), 325–335 (2002)
Mendel, J.M., Zadeh, L.A., Yager, R.R., Lawry, J., Hagras, H., Guadarrama, S.: What computing with words means to me. IEEE Computational Intelligence Magazine 5(1), 20–26 (2010)
Mizumoto, M., Tanaka, K.: Some properties of fuzzy sets of type 2. Information Control 31, 312–340 (1976)
Parsons, S.: Current approaches to handling imperfect information in data and knowledge bases. IEEE Transactions on Knowledge Data Engineering 8(3), 353–372 (1996)
Rodríguez, R.M., Espinilla, M., Sanchez, P.J., Martínez, L.: Using linguistic incomplete preference relations to cold start recommendations. Internet Research 20(3), 296–315 (2010)
Rodríguez, R.M., Martínez, L., Herrera, F.: Hesitant fuzzy linguistic term sets for decision making. IEEE Transactions on Fuzzy Systems (2011), doi:10.1109/TFUZZ, 2170076
Sengupta, A., Kumar Pal, T.: On comparing interval numbers. European Journal of Operational Research 127, 28–43 (2000)
Torra, V.: Negation functions based semantics for ordered linguistic labels. International Journal of Intelligent Systems 11, 975–988 (1996)
Torra, V.: Hesitant fuzzy sets. International Journal of Intelligent Systems 25(6), 529–539 (2010)
Türkşen, I.B.: Type 2 representation and reasoning for CWW. Fuzzy Sets and Systems 127, 17–36 (2002)
Wang, J.H., Hao, J.: A new version of 2-tuple fuzzy linguistic representation model for computing with words. IEEE Transactions on Fuzzy Systems 14(3), 435–445 (2006)
Yager, R.R.: On the theory of bags. International Journal Generation System 13, 23–37 (1986)
Yager, R.R.: An approach to ordinal decision making. International Joumal of Approximate Reasoning 12(3-4), 237–261 (1995)
Zadeh, L.: Fuzzy sets. Information and Control 8, 338–353 (1965)
Zadeh, L.: The concept of a linguistic variable and its applications to approximate reasoning. Information Sciences, Part I, II, III (8,9), 199–249, 301–357, 43–80 (1975)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rodríguez, R.M., Martínez, L., Herrera, F. (2011). Hesitant Fuzzy Linguistic Term Sets. In: Wang, Y., Li, T. (eds) Foundations of Intelligent Systems. Advances in Intelligent and Soft Computing, vol 122. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25664-6_34
Download citation
DOI: https://doi.org/10.1007/978-3-642-25664-6_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25663-9
Online ISBN: 978-3-642-25664-6
eBook Packages: EngineeringEngineering (R0)