An advanced dice similarity measure of generalized fuzzy numbers and its application in multicriteria decision making

References

• Ahmad, S. A. S., Mohamad, D., Sulaiman, N. H., Shariff, J. M., & Abdullah, K. (2018, June). A distance and set theoretic-based similarity measure for generalized trapezoidal fuzzy numbers. In AIP Conference Proceedings (Vol. 1974, No. 1, p. 020043). AIP Publishing.
   Google Scholar
• Baccour, L. (2018). New intuitionistic fuzzy similarity and distance measures applied to multi-criteriadecision making. Mechatronic Systems and Control, 46(1), 1–7.
   Web of Science ®Google Scholar
• Beg, I., & Rashid, T. (2017). A fuzzy similarity measure based on equivalence relation with application in cluster analysis. International Journal of Computers and Applications, 39(3), 148–154. doi:10.1080/1206212X.2017.1309220
   Google Scholar
• Chen, S. H. (1985). Ranking fuzzy numbers with maximizing set and minimizing set. Fuzzy Sets and Systems, 17(2), 113–129. doi:10.1016/0165-0114(85)90050-8
   Web of Science ®Google Scholar
• Chen, S. J., & Chen, S. M. (2001, December). A new method to measure the similarity between fuzzy numbers. In 10th IEEE International Conference on Fuzzy Systems (Cat. No. 01CH37297) (Vol. 3, pp. 1123–1126). IEEE.
   Google Scholar
• Chen, S. J., & Hwang, C. L. (1992). Fuzzy multiple attribute decision making methods. In Shu-Jen Chen, Ching-Lai Hwang (Eds.), Fuzzy multiple attribute decision making (pp. 289–486). Berlin, Heidelberg: Springer.
   Google Scholar
• Chen, S. M. (1996). New methods for subjective mental workload assessment and fuzzy risk analysis. Cybernetics and Systems, 27(5), 449–472. doi:10.1080/019697296126417
   Web of Science ®Google Scholar
• Chen, S. M., Munif, A., Chen, G. S., Liu, H. C., & Kuo, B. C. (2012). Fuzzy risk analysis based on ranking generalized fuzzy numbers with different left heights and right heights. Expert Systems with Applications, 39(7), 6320–6334. doi:10.1016/j.eswa.2011.12.004
   Web of Science ®Google Scholar
• Chutia, R., & Gogoi, M. K. (2018). Fuzzy risk analysis in poultry farming based on a novel similarity measure of fuzzy numbers. Applied Soft Computing, 66, 60–76. doi:10.1016/j.asoc.2018.02.008
   Web of Science ®Google Scholar
• Dhivya, J., & Sridevi, B. (2019). A novel similarity measure between intuitionistic fuzzy sets based on the mid points of transformed triangular fuzzy numbers with applications to pattern recognition and medical diagnosis. Applied Mathematics-A Journal of Chinese Universities, 34(2), 229–252. doi:10.1007/s11766-019-3708-x
   Google Scholar
• Dice, L. R. (1945). Measures of the amount of ecologic association between species. Ecology, 26(3), 297–302. doi:10.2307/1932409
   Web of Science ®Google Scholar
• Dutta, P., & Hazarika, G. C. (2017). Construction of families of probability boxes and corresponding membership functions at different fractiles. Expert Systems, 34(3), e12202. doi:10.1111/exsy.12202
   Web of Science ®Google Scholar
• Fei, L., Wang, H., Chen, L., & Deng, Y. (2019). A new vector valued similarity measure for intuitionistic fuzzy sets based on OWA operators. Iranian Journal of Fuzzy Systems, 16(3), 113–126.
   Web of Science ®Google Scholar
• Garg, H. (2018). An improved cosine similarity measure for intuitionistic fuzzy sets and their applications to decision-making process. Hacettepe Journal of Mathematics and Statistics, 47(6), 1578–1594. doi:10.15672/HJMS.2017.510
   Web of Science ®Google Scholar
• Hejazi, S. R., Doostparast, A., & Hosseini, S. M. (2011). An improved fuzzy risk analysis based on a new similarity measures of generalized fuzzy numbers. Expert Systems with Applications, 38(8), 9179–9185. doi:10.1016/j.eswa.2011.01.101
   Web of Science ®Google Scholar
• Hesamian, G. (2017). Fuzzy similarity measure based on fuzzy sets. Control and Cybernetics, 46, 71–86.
   Google Scholar
• Hesamian, G., & Chachi, J. (2017). On similarity measures for fuzzy sets with applications to pattern recognition, decision making, clustering, and approximate reasoning. Journal of Uncertain Systems, 11(1), 35–48.
   Google Scholar
• Hsieh, C. H. (1999). (1999). Similarity of generalized fuzzy numbers with graded mean integration representation. Proc. 8th Int. Fuzzy Systems Association World Congr, 2, 551–555.
   Google Scholar
• Jaccard, P. (1901). Distribution de la flore alpine dans le bassin des Dranses et dans quelques régions voisines. Bull Soc Vaudoise Sci Nat, 37, 241–272.
   Google Scholar
• Khorshidi, H. A., & Nikfalazar, S. (2017). An improved similarity measure for generalized fuzzy numbers and its application to fuzzy risk analysis. Applied Soft Computing, 52, 478–486. doi:10.1016/j.asoc.2016.10.020
   Web of Science ®Google Scholar
• Lee, H. S. (2002). Optimal consensus of fuzzy opinions under group decision making environment. Fuzzy Sets and Systems, 132(3), 303–315. doi:10.1016/S0165-0114(02)00056-8
   Web of Science ®Google Scholar
• Liu, D., Chen, X., & Peng, D. (2018). Cosine similarity measure between hybrid intuitionistic fuzzy sets and its application in medical diagnosis. Computational and Mathematical Methods in Medicine, 2018, 1–7. doi:10.1155/2018/3146873
   Web of Science ®Google Scholar
• Luo, M., & Liang, J. (2018). A novel similarity measure for interval-valued intuitionistic fuzzy sets and its applications. Symmetry, 10(10), 441. doi:10.3390/sym10100441
   Google Scholar
• Mo, H., & Deng, Y. (2018). A new MADA methodology based on D numbers. International Journal of Fuzzy Systems, 20(8), 2458–2469.
   Web of Science ®Google Scholar
• Patra, K., & Mondal, S. K. (2015). Fuzzy risk analysis using area and height based similarity measure on generalized trapezoidal fuzzy numbers and its application. Applied Soft Computing, 28, 276–284. doi:10.1016/j.asoc.2014.11.042
   Web of Science ®Google Scholar
• Peng, X., & Garg, H. (2019). Multiparametric similarity measures on Pythagorean fuzzy sets with applications to pattern recognition. Applied Intelligence, 49(12), 4058–4096. doi:10.1007/s10489-019-01445-0
   Web of Science ®Google Scholar
• Phan, T. T. H., Bigand, A., & Caillault, E. P. (2018). A new fuzzy logic-based similarity measure applied to large gap imputation for uncorrelated multivariate time series. Applied Computational Intelligence and Soft Computing, 2018, 1–15. doi:10.1155/2018/9095683
   Web of Science ®Google Scholar
• Salton, G., & McGill, M.J. (1987). Introduction to Modern Information Retrieval. New York, NY: McGraw-Hill.
   Google Scholar
• Singhal, N., Verma, A., & Chouhan, U. (2018). An application of similarity measure of fuzzy soft sets in verndor selection problem. Materials Today: Proceedings, 5(2), 3987–3993. doi:10.1016/j.matpr.2017.11.657
   Google Scholar
• Song, Y., Wang, X., Quan, W., & Huang, W. (2019). A new approach to construct similarity measure for intuitionistic fuzzy sets. Soft Computing, 23(6), 1985–1998. doi:10.1007/s00500-017-2912-0
   Web of Science ®Google Scholar
• Tourad, M. C., & Abdali, A. (2018). An intelligent similarity model between generalized trapezoidal fuzzy numbers in large scale. International Journal of Fuzzy Logic and Intelligent Systems, 18(4), 303–315. doi:10.5391/IJFIS.2018.18.4.303
   Web of Science ®Google Scholar
• Wang, X., Wang, J., & Chen, X. (2016). Fuzzy multi-criteria decision making method based on fuzzy structured element with incomplete weight information. Iranian Journal of Fuzzy Systems, 13(2), 1–17.
   Web of Science ®Google Scholar
• Wei, G. (2018). Some similarity measures for picture fuzzy sets and their applications. Iranian Journal of Fuzzy Systems, 15(1), 77–89.
   Web of Science ®Google Scholar
• Wei, S. H., & Chen, S. M. (2009). A new approach for fuzzy risk analysis based on similarity measures of generalized fuzzy numbers. Expert Systems with Applications, 36(1), 589–598. doi:10.1016/j.eswa.2007.09.033
   Web of Science ®Google Scholar
• Xu, L., & Yang, J. B. (2001). Introduction to multi-criteria decision making and the evidential reasoning approach (pp. 1–21). Manchester: Manchester School of Management.
   Google Scholar
• Xu, Z., Shang, S., Qian, W., & Shu, W. (2010). A method for fuzzy risk analysis based on the new similarity of trapezoidal fuzzy numbers. Expert Systems with Applications, 37(3), 1920–1927. doi:10.1016/j.eswa.2009.07.015
   Web of Science ®Google Scholar
• Ye, J. (2011). Cosine similarity measures for intuitionistic fuzzy sets and their applications. Mathematical and Computer Modelling, 53(1–2), 91–97. doi:10.1016/j.mcm.2010.07.022
   Web of Science ®Google Scholar
• Ye, J. (2012). The Dice similarity measure between generalized trapezoidal fuzzy numbers based on the expected interval and its multicriteria group decision-making method. Journal of the Chinese Institute of Industrial Engineers, 29(6), 375–382. doi:10.1080/10170669.2012.710879
   Google Scholar
• Yong, D., Wenkang, S., Feng, D., & Qi, L. (2004). A new similarity measure of generalized fuzzy numbers and its application to pattern recognition. Pattern Recognition Letters, 25(8), 875–883. doi:10.1016/j.patrec.2004.01.019
   Web of Science ®Google Scholar
• Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. doi:10.1016/S0019-9958(65)90241-X
   Google Scholar
• Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning–I. Information Sciences, 8(3), 199–249. doi:10.1016/0020-0255(75)90036-5
   Web of Science ®Google Scholar
• Zizovic, M. M., Damljanovic, N., & Zizovic, M. R. (2017). Multi-criteria decision making method for models with the dominant criterion. Filomat, 31(10), 2981–2989. doi:10.2298/FIL1710981Z
   Web of Science ®Google Scholar