Abstract
Recently, Artificial Intelligence (AI) has become more and more popular and important in real life and consists of many research fields such as language recognition, image recognition, natural language processing and expert systems.
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References
Chiclana F, Herrera F, Herrera-Viedma E (1998) Integrating three representation models in fuzzy multipurpose decision making based on fuzzy preference relations. Fuzzy Sets Syst 97:33–48
Chiclana F, Herrera-Viedma E, Alonso S, Herrera F (2009) Cardinal consistency of reciprocal preference relations: a characterization of multiplicative transitivity. IEEE Trans Fuzzy Syst 17(1):14–23
Dong YC, Xu YF, Li HY (2008) On consistency measures of linguistic preference relations. Eur J Oper Res 189(2):430–444
Dubois D (2011) The role of fuzzy sets indecision sciences: old techniques and new directions. Fuzzy Sets Syst 184:3–28
Fu ZG, Liao HC (2019) Unbalanced double hierarchy linguistic term set: the TOPSIS method for multi-expert qualitative decision making involving green mine selection. Inf Fusion 51:271–286
González-Pachón J, Romero C (2001) Aggregation of partial ordinal rankings: an interval goal programming approach. Comput Oper Res 28:827–834
Gou XJ, Liao HC, Xu ZS, Herrera F (2017) Double hierarchy hesitant fuzzy linguistic term set and MULTIMOORA method: a case of study to evaluate the implementation status of haze controlling measures. Inf Fusion 38:22–34
Gou XJ, Liao HC, Xu ZS, Min R, Herrera F (2019) Group decision making with double hierarchy hesitant fuzzy linguistic preference relations: consistency based measures, index and repairing algorithms and decision model. Inf Sci 489:93–112
Gou XJ, Xu ZS, Herrera F (2018a) Consensus reaching process for large-scale group decision making with double hierarchy hesitant fuzzy linguistic preference relations. Knowl-Based Syst 157:20–33
Gou XJ, Xu ZS, Liao HC, Herrera F (2018b) Multiple criteria decision making based on distance and similarity measures with double hierarchy hesitant fuzzy linguistic environment. Comput Ind Eng 126:516–530
Gou XJ, Xu ZS, Liao HC, Herrera F (2020a) A consensus model to manage minority opinions and noncooperative behaviors in large-scale GDM with double hierarchy linguistic preference relations. IEEE Trans Cybern. https://doi.org/10.1109/TCYB.2020.2985069
Gou XJ, Xu ZS, Zhou W (2020b) Managing consensus by multiple stages optimization models with linguistic preference orderings and double hierarchy linguistic preferences. Technol Econ Dev Econ 26(3):642–674
He Y, Xu ZS (2018) A consensus framework with different preference ordering structures and its applications in human resource selection. Comput Ind Eng 118:80–88
Herrera F, MartÃnez L (2000) A 2-tuple fuzzy linguistic representation model for computing with words. IEEE Trans Fuzzy Syst 8(6):746–752
Hervés-Beloso C, Cruces HV (2018) Continuous preference orderings representable by utility functions. J Econ Surv 33(1):179–194
Liang HM, Xiong W, Dong YC (2018) A prospect theory-based method for fusing the individual preference-approval structures in group decision making. Comput Ind Eng 117:237–248
Millet I (1997) The effectiveness of alternative preference elicitation methods in the analytic hierarchy process. J Multi-Criteria Decis Anal 6:41–51
Montserrat-Adell J, Xu ZS, Gou XJ, Agell N (2019) Free double hierarchy hesitant fuzzy linguistic term sets: an application on raking alternatives in GDM. Inf Fusion 47:45–59
RodrÃguez RM, MartÃnez L, Herrera F (2012) Hesitant fuzzy linguistic terms sets for decision making. IEEE Trans Fuzzy Syst 20:109–119
Schubert J (1995) On p in a decision-theoretic apparatus of Dempster-Shafer theory. Int J Approx Reason 13:185–200
Tanino T (1984) Fuzzy preference orderings in group decision making. Fuzzy Sets Syst 12:117–131
Wang XD, Gou XJ, Xu ZS (2020) Assessment of Traffic congestion with ORESTE method under double hierarchy hesitant fuzzy linguistic term set. Appl Soft Comput 86:105864
Wang H, Xu ZS, Zeng XJ (2018) Linguistic terms with weakened hedges: a model for qualitative decision making under uncertainty. Inf Sci 433:37–45
Xia MM, Xu ZS (2011) Hesitant fuzzy information aggregation in decision making. Int J Approx Reason 52:395–407
Xu ZS (2004a) A method based on linguistic aggregation operators for group decision making with linguistic preference relations. Inf Sci 166(1–4):19–30
Xu ZS (2004b) Uncertain linguistic aggregation operators based approach to multiple attribute group decision making under uncertain linguistic environment. Inf Sci 168(1–4):171–184
Xu ZS (2005) Deviation measures of linguistic preference relations in group decision making. Omega 33(3):249–254
Xu ZS (2013) Group decision making model and approach based on interval preference orderings. Comput Ind Eng 64:797–803
Xu ZS, Wang H (2017) On the syntax and semantics of virtual linguistic terms for information fusion in decision making. Inf Fusion 34:43–48
Yager RR (2004) On the retranslation process in Zadeh’s paradigm of computing with words. IEEE Trans Syst Man Cybern Part B Cybern 34(2):1184–1195
Zadeh LA (2012) Computing with words: what is computing with words (CWW)?. Springer, Berlin, Heidelberg
Zhang BW, Liang HM, Zhang GQ, Xu YF (2018a) Minimum deviation ordinal consensus reaching in GDM with heterogeneous preference structures. Appl Soft Comput 67:658–676
Zhang BW, Liang HM, Gao Y, Zhang GQ (2018b) The optimization-based aggregation and consensus with minimum-cost in group decision making under incomplete linguistic distribution context. Knowl-Based Syst 162:92–102
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Gou, X., Xu, Z. (2021). Double Hierarchy Linguistic Term Set and Its Extensions. In: Double Hierarchy Linguistic Term Set and Its Extensions. Studies in Fuzziness and Soft Computing, vol 396. Springer, Cham. https://doi.org/10.1007/978-3-030-51320-7_1
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DOI: https://doi.org/10.1007/978-3-030-51320-7_1
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