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Soft Computing
Erschienen in: Soft Computing 12/2017

30.12.2015 | Methodologies and Application

Dual hesitant fuzzy rough set and its application

verfasst von: Haidong Zhang, Lan Shu, Shilong Liao, Cairang Xiawu

Erschienen in: Soft Computing | Ausgabe 12/2017

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Abstract

In this paper, we propose a general framework for the study of dual hesitant fuzzy rough sets integrating rough set theory with dual hesitant fuzzy set theory in which both constructive and axiomatic approaches are considered. In a constructive approach, by using a dual hesitant fuzzy relation, lower and upper dual hesitant fuzzy rough approximation operators with respect to a dual hesitant fuzzy approximation space are first defined and some properties of this model are further discussed. Adopting an axiomatic approach, dual hesitant fuzzy rough approximation operators are defined by axioms. And different axiom sets of dual hesitant fuzzy set-theoretic operators guarantee the existence of different types of dual hesitant fuzzy relations producing the same operators. We then give an approach of decision-making in uncertainty environment by using the dual hesitant fuzzy rough sets. Finally, a practical application in medical diagnosis is provided to illustrate the validity of this approach.
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Literatur
Chakrabarty K, Gedeon T, Koczy L (1998) Intuitionistic fuzzy rough set. In: Proceedings of 4th joint conference on information sciences (JCIS), Durham, pp 211–214
Chen N, Xu ZS, Xia MM (2013) Correlation coefficients of hesitant fuzzy sets and their applications to clustering analysis. Appl Math Model 37:2197–2211MathSciNetCrossRefMATH
Chen YF, Peng XD, Guan GH, Jiang HD (2014) Approaches to multiple attribute decision making based on the correlation coefficient with dual hesitant fuzzy information. J Intell Fuzzy Syst 26:2547–2556MathSciNetMATH
Cornelis C, Cock MD, Kerre EE (2003) Intuitionistic fuzzy rough sets: at the crossroads of imperfect knowledge. Expert Syst Appl 20:260–270CrossRef
Dubois D, Prade H (1990) Rough fuzzy sets and fuzzy rough sets. Int J Gen Syst 17:191–209CrossRefMATH
Farhadinia B (2013) Information measures for hesitant fuzzy sets and interval-valued hesitant fuzzy sets. Inf Sci 240:129–144MathSciNetCrossRefMATH
Farhadinia B (2014) Correlation for dual hesitant fuzzy sets and dual interval-valued hesitant fuzzy Sets. Int J Intell Syst 29:184–205CrossRef
Gong ZT, Sun BZ (2008) Probability rough sets model between different universes and its applications. In: International Conference on Machine Learning and Cybernetics, pp 561–565
Jena SP, Ghosh SK (2002) Intuitionistic fuzzy rough sets. Notes Intuitionistic Fuzzy Sets 8:1–18MathSciNetMATH
Liang DC, Liu D (2015) A novel risk decision-making based on decision-theoretic rough sets under hesitant fuzzy information. IEEE Trans Fuzzy Syst 23(2):237–247CrossRef
Liang DC, Liu D (2015) Deriving three-way decisions from intuitionistic fuzzy decision-theoretic rough sets. Inf Sci 300:28–48MathSciNetCrossRefMATH
Liao HC, Xu ZS (2013) A VIKOR-based method for hesitant fuzzy multi-criteria decision making. Fuzzy Optim Decis Mak 12:373–392
Liu GL (2010) Rough set theory based on two universal sets and its applications. Knowl Based Syst 23(2):110–115CrossRef
Miyamoto S (2000) Multisets and fuzzy multisets. In: Liu ZQ, Miyamoto S (eds) Soft computing and human-centered machines. Springer, Berlin, pp 9–33CrossRef
Pawlak Z (1991) Rough sets-theoretical aspects to reasoning about data. Kluwer Academic Publisher, BostonMATH
Rizvi S, Naqvi HJ, Nadeem D (2002) Rough intuitionistic fuzzy set. In: Proceedings of the Sixth Joint Conference on Information Sciences (JCIS), Durham, pp 101–104
Rodrguez RM, Martnez L, Herrera F (2012) Hesitant fuzzy linguistic term sets for decision making. IEEE Trans Fuzzy Syst 1:109–119CrossRef
Samanta SK, Mondal TK (2001) Intuitionistic fuzzy rough sets and rough intuitionistic fuzzy sets. J Fuzzy Math 9:561–582MathSciNetMATH
Shen YH, Wand FX (2011) Variable precision rough set model over two universes and its properties. Soft Comput 15(3):557–567CrossRefMATH
Sun BZ, Gong ZT, Chen DG (2008) Fuzzy rough set theory for the interval-valued fuzzy information systems. Inf Sci 178:2794–2815MathSciNetCrossRefMATH
Sun BZ, Ma WM, Liu Q (2013) An approach to decision making based on intuitionistic fuzzy rough sets over two universes. J Oper Res Soc 64:1079–1089CrossRef
Szmidt E, Kacprzyk J (2002) An intuitionistic fuzzy set based approach to intelligent data analysis: an application to medical diagnosis. In: Abraham A, Jain L, Kacprzyk J (eds) Recent advances in intelligent paradigms and and applications. Springer-Verlag, pp 57–70
Szmidt E, Kacprzyk J (2004) A similarity measure for intuitionistic fuzzy sets and its application in supporting medical diagnostic reasoning. Lect Notes Artif Intell 3070:388–393MATH
Thiele H (2001) On aximatic characterisation of fuzzy approximation operators: II. The rough fuzzy set based case. In: Proceeding of the 31st IEEE international symposium on multiple-valued logic, pp 330–335
Torra V (2010) Hesitant fuzzy sets. Int J Intell Syst 25:529–539MATH
Torra V, Narukawa Y (2009) On hesitant fuzzy sets and decision. In: The 18th IEEE international conference on fuzzy systems, Jeju Island, pp 1378–1382
Wang HJ, Zhao XF, Wei GW (2014) Dual hesitant fuzzy aggregation operators in multiple attribute decision making. J Intell Fuzzy Syst 26:2281–2290MathSciNetMATH
Wu WZ, Leung Y, Mi JS (2005) On characterizations of \(({\cal I\cal ,\cal {T}})\)-fuzzy rough approximation operators. Fuzzy Sets Syst 154:76–102
Wu WZ, Leung Y, Zhang WX (2006) On generalized rough fuzzy approximation operators. Transactions on Rough sets V, Lecture Notes in Computer Science 4100:263–284
Xu ZS, Xia MM (2011a) Distance and similarity measures for hesitant fuzzy sets. Inf Sci 181:2128–2138
Xu ZS, Xia MM (2011b) On distance and correlation measures of hesitant fuzzy information. Int J Intell Syst 26:410–425
Xu ZS, Zhang X (2013) Hesitant fuzzy multi-attribute decision making based on TOPSIS with incomplete weight information. Knowl Based Syst 52:53–64CrossRef
Yan RX, Zheng JG, Liu JL, Zhai YM (2010) Research on the model of rough set over dual-universes. Knowl Based Syst 23(8):817–822CrossRef
Yang HL, Li SG, Wang SY, Wang J (2012a) Bipolar fuzzy rough set model on two different universes and its application. Knowl Based Syst 35:94–101
Yang HL, Li SG, Guo ZL, Ma CH (2012b) Transformation of bipolar fuzzy rough set models. Knowl Based Syst 27:60–68
Yang XB, Song XN, Qi YS, Yang JY (2014) Constructive and axiomatic approaches to hesitant fuzzy rough set. Soft Comput 18:1067–1077CrossRefMATH
Ye J (2014) Correlation coefficient of dual hesitant fuzzy sets and its application to multiple attribute decision making. Appl Math Model 38:659–666MathSciNetCrossRef
Yeung DS, Chen DG, Tsang ECC, Lee JWT, Wang XZ (2005) On the generalization of fuzzy rough sets. IEEE Trans Fuzzy Syst 13:343–361CrossRef
Zhang HY, Zhang WX, Wu WZ (2009) On characterization of genernalized interval-valued fuzzy rough sets on two universes of discourse. Int J Approx Reason 51:56–70CrossRefMATH
Zhang N, Wei G (2013) Extension of VIKOR method for decision making problem based on hesitant fuzzy set. Appl Math Model 37(7):4938–4947MathSciNetCrossRef
Zhang XL, Xu ZS (2014) The TODIM analysis approach based on novel measured functions under hesitant fuzzy environment. Knowl Based Syst 61:48–58CrossRef
Zhou L, Wu WZ (2008) On genernalized intuitionistic fuzzy approximation operators. Inf Sci 178:2448–2465MATH
Zhou L, Wu WZ (2009) On characterization of intuitonistic fuzzy rough sets based on intuitionistic fuzzy implicators. Inf Sci 179:883–898CrossRefMATH
Zhu B, Xu ZS, Xia MM (2012) Dual hesitant fuzzy sets. J Appl Math, Article ID 879629, p 13
Metadaten
Titel
Dual hesitant fuzzy rough set and its application
verfasst von
Haidong Zhang
Lan Shu
Shilong Liao
Cairang Xiawu
Publikationsdatum
30.12.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 12/2017
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-015-2008-7

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