Abstract
The operational laws of intuitionistic fuzzy numbers are useful in dealing with the problems under intuitionistic fuzzy circumstances. As a supplementation, the exponential operational law of intuitionistic fuzzy numbers has been defined. Consider that we may utilize interval-valued intuitionistic fuzzy numbers (IVIFNs) to express uncertain weight information comprehensively in the complex multi-attribute decision making problems, in this paper, we discuss two exponential operational laws of IVIFNs, namely, the exponential operational law of IVIFNs with crisp parameter and the exponential operational law of IVIFNs with interval-valued parameter. Several properties and aggregation methods based on the exponential operational laws are discussed. Furthermore, we propose a new method to compare the novel dual interval-valued intuitionistic fuzzy numbers. Additionally, we give two information aggregation methods over these two exponential operational laws for dealing with some special problems in multi-attribute decision making, and finally, we apply the methods to a practical problem involving the choice of the optimal powered roof support for coal extraction with a high recovery rate.
Similar content being viewed by others
References
Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–356
Atanassov KT, Pasi G, Yager RR (2005) Intuitionistic fuzzy interpretations of multi-criteria multi-person and multi-measurement tool decision making. Int J Syst Sci 36:859–868
Vlachos KI, Sergiadis GD (2007) Intuitionistic fuzzy information-applications to pattern recognition. Pattern Recogn Lett 28:197–206
Khatibi V, Montazer GA (2009) Intuitionistic fuzzy set vs. fuzzy set application in medical pattern recognition. Artif Intell Med 47:43–52
Wang XZ, Xing HJ, Li Y (2014) A study on relationship between generalization abilities and fuzziness of base classifiers in ensemble learning. IEEE Trans Fuzzy Syst. doi:10.1109/TFUZZ.2014.2371479
Wang XZ, Dong LC, Yan JH (2012) Maximum ambiguity based sample selection in fuzzy decision tree induction. IEEE Trans Knowl Data Eng 24(8):1491–1505
Wang XZ, Dong CR (2009) Improving generalization of fuzzy if–then rules by maximizing fuzzy entropy. IEEE Trans Fuzzy Syst 17(3):556–567
Szmidt E, Kacprzyk J (2004) A similarity measure for intuitionistic fuzzy sets and its application in supporting medical diagnostic reasoning. Lect Notes Comput Sci 3070:388–393
Atanassov KT (1986) Intuitionistic fuzzy set. Fuzzy Sets Syst 20:87–96
Xu YJ, Wang HM (2012) The induced generalized aggregation operators for intuitionistic fuzzy sets and their application in group decision making. Appl Soft Comput 12(3):1168–1179
Hashemi H, Bazargan J, Mousavi SM (2013) A compromise ratio method with an application to water resources management: an intuitionistic fuzzy set. Water Resour Manage 27(7):2029–2051
Yu DJ (2013) Prioritized information fusion method for triangular intuitionistic fuzzy set and its application to teaching quality evaluation. Int J Intell Syst 28(5):411–435
Mazandarani M, Najariyan M (2014) Type-2 fuzzy fractional derivatives. Commun Nonlinear Sci Numer Simul 19:2354–2372
Mazandarani M, Najariyan M (2014) Differentiability of type-2 fuzzy number-valued functions. Commun Nonlinear Sci Numer Simul 19:710–725
Atanassov KT, Gargov G (1989) Interval-valued intuitionistic fuzzy sets. Fuzzy Sets Syst 31:343–349
Xu ZS, Chen J (2007) On geometric aggregation over interval-valued intuitionistic fuzzy information. In: The 4th international conference on fuzzy systems and knowledge discovery (FSKD‘07), Haikou, China, vol 2, pp 466–471
Xu ZS, Cai XQ (2015) Group decision making with incomplete interval-valued intuitionistic preference relations. Group Decis Negot 24:193–215
Qi XW, Liang CY, Zhang JL (2015) Generalized cross-entropy based group decision making with unknown expert and attribute weights under interval-valued intuitionistic fuzzy environment. Comput Ind Eng 79:52–64
Chen TY (2015) The inclusion-based TOPSIS method with interval-valued intuitionistic fuzzy sets for multiple criteria group decision making. Appl Soft Comput 26:57–73
Wei CP, Zhang YZ (2015) Entropy measures for interval-valued intuitionistic fuzzy sets and their application in group decision-making. Math Probl Eng. doi:10.1155/2015/563745
Park JH, Lim KM, Lee BY (2015) Relationship between subsethood measure and entropy of interval-valued intuitionistic fuzzy sets. J Comput Anal Appl 18:357–370
Xu JP, Shen F (2014) A new outranking choice method for group decision making under Atanassov’s interval-valued intuitionistic fuzzy environment. Knowl-Based Syst 70:177–188
Chen TY (2014) The inclusion-based LINMAP method for multiple criteria decision analysis within an interval-valued Atanassov’s intuitionistic fuzzy environment. Int J Inf Technol Dec Mak 13:1325–1360
Wu J, Chiclana F (2014) A risk attitudinal ranking method for interval-valued intuitionistic fuzzynumbers based on novel attitudinal expected score and accuracy functions. Appl Soft Comput 22:272–286
Parvathi R, Malathi C (2012) Arithmetic operations on symmetric trapezoidal intuitionistic fuzzy numbers. Int J Soft Comput Eng 2:268–273
Wan SP (2013) Power average operators of trapezoidal intuitionistic fuzzy numbers and application to multi-attribute group decision making. Appl Math Model 37:4112–4126
De SK, Biswas R, Roy AR (2000) Some operations on intuitionistic fuzzy sets. Fuzzy Sets Syst 114:477–484
Xu ZS, Yager RR (2006) Some geometric aggregation operators based on intuitionistic fuzzy sets. Int J Gen Syst 35:417–433
Xu ZS (2007) Intuitionistic fuzzy aggregation operations. IEEE Trans Fuzzy Syst 15:1179–1187
Atanassov KT, Riěcan B (2006) On two operations over intuitionistic fuzzy sets. J Appl Math Stat Informat 2:145–148
Gou XJ, Xu ZS, Lei Q (2015) New operational laws and aggregation method of intuitionistic fuzzy information. J Intell Fuzzy Syst. doi:10.3233/IFS-151739
Xu ZS, Cai XQ (2012) Intuitionistic fuzzy information aggregation: theory and applications. Science Press, Beijing; Springer, Berlin
Xu ZS, Cai XQ (2010) Recent advances in intuitionistic fuzzy information aggregation. Fuzzy Optim Decis Making 9:359–381
Liao HC, Xu ZS (2014) Intuitionistic fuzzy hybrid weighted aggregation operators. Int J Intell Syst 29:971–993
Xu RN, Zhai XY (1992) Extensions of the analytic hierarchy process in fuzzy environment. Fuzzy Sets Syst 52:251–257
Xu ZS (2007) The aggregation method of interval-valued intuitionistic fuzzy information and appliation in decision making. Control Dec 22:215–219
Wang ZJ, Li KW, Wang WZ (2009) An approach to multiattribute decision making with interval-valued intuitionistic fuzzy assessments and incomplete weights. Inf Sci 179:3026–3040
Masoumi I, Naraghi F, Rashidi-nejad F, Masoumi S (2014) Application of fuzzy multi-attribute decision making to select and to rank the post-mining land-use. Environ Earth Sci 72:221–231
Da QL, Liu XW (1999) Interval number linear programming and the satisfactory solution. Syst Eng Theory Pract 19:3–7
Xu ZS (2001) An algorithm of the ranking of fuzzy complementary judgment matrix. J Syst Eng 16:311–314
Zhang XM, Xu ZS (2012) A new method for ranking intuitionistic fuzzy values and its application in multi-attribute decision making. Fuzzy Optim Dec Making 11:135–146
Barczak TM (1990) Selecting proper type of shield supports. Information Circular, Bureau of Mines
Wiklund B, Kizil MS, Canbulat I (2011) Development of a cavity prediction model for longwall mining. In: Aziz N (ed) Proceedings of the 11th underground coal operators’ conference, Wollongong, NSW, Australia, University of Wollongong, pp 48–59
Acknowledgments
This research was funded by the National Natural Science Foundation of China (No. 61273209), and the Central University Basic Scientific Research Business Expenses Project (No. skgt201501).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Gou, X., Xu, Z. & Liao, H. Exponential operations of interval-valued intuitionistic fuzzy numbers. Int. J. Mach. Learn. & Cyber. 7, 501–518 (2016). https://doi.org/10.1007/s13042-015-0434-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13042-015-0434-6