Fuzzy risk analysis using a new technique of ranking of generalized trapezoidal fuzzy numbers
Tóm tắt
Ranking of generalized trapezoidal fuzzy number is very important to order the fuzzy numbers. In this propose paper a new approach has been introduced for ranking of generalized trapezoidal fuzzy numbers. In this new technique the mean position, area and perimeter of the fuzzy numbers has been considered as major factors. Some properties corresponding to the new proposed method have been discussed. There are some existing techniques of ranking generalized trapezoidal fuzzy numbers. But some lacunas exist in their proposed methods. It has been compared with existing different techniques of generalized trapezoidal fuzzy numbers and has been overcome the drawbacks of those existing methods by our new method. Finally, a risk analysis of a selection of production house has been shown to show the effectiveness of the proposed method.
Tài liệu tham khảo
Abbasbandy S, Hajjari T (2009) A new approach for ranking of trapezoidal fuzzy numbers. Comput Math Appl 57(3):413–419
Asady B (2010) The revised method of ranking L-R fuzzy number based on deviation degree. Expert Syst Appl 37(7):5056–5060
Chen SM, Chang CH (2016) Fuzzy multiattribute decision making based on transformation techniques of intuitionistic fuzzy values and intuitionistic fuzzy geometric averaging operators. Inform Sci 352:133–149
Chen SH, Chen SM (2006) A new method for ranking generalized fuzzy numbers handling fuzzy risk analysis problems. In Proceedings of the 9-th joint conferece on Information Sciences, Kaohsiung, Taiwan, Republic of China.(pp 1196–1199)
Chen SJ, Chen SM (2003) Fuzzy risk analysis based on similarity measures of generalized fuzzy numbers. IEEE Trans Fuzzy Syst 11(1):45–56
Chen SJ, Chen SM (2007) Fuzzy risk analysis based on the ranking of generalized trapezoidal fuzzy numbers. Appl Intell 26(1):1–11
Chen SM, Chen JH (2009) Fuzzy risk analysis based on ranking generalized fuzzy numbers with different heights and different spreads. Expert Syst Appl 36(3, Part 2) (2009) 6833–6842
Chen SM, Chiou CH (2014) Multiattribute Decision Making Based on Interval-Valued Intuitionistic Fuzzy Sets. PSO Techn Evident Reason Methodol IEEE Trans Fuzzy Syst 23(6):1905–1916
Chen SM, Hsiao WH, Jong WT (1997) Bidirectional approximate reasoning based on interval-valued fuzzy sets. Fuzzy Sets Syst 91(3):339–353
Chen SM, Hsiao WH (2000) Bidirectional approximate reasoning for rule-based systems using interval-valued fuzzy sets. Fuzzy Sets Syst 113(2):185–203
Chen SM, Sanguansat K (2011) Analyzing fuzzy risk based on similarity measures between interval-valued fuzzy numbers. Expert Syst Appl 38(2011):8612–8621
Chen SM (2011) Sanguansat K (2011) Analyzing fuzzy risk based on a new fuzzy ranking method between generalized fuzzy numbers. Expert Syst Appl 38(3):2163–2171
Cheng CH (1998) A new approach for ranking fuzzy numbers by distance method. Fuzzy Sets Syst 95(3):307–317
Chutia R, Chutia B (2017) A new method of ranking parametric form of fuzzy numbers using value and ambiguity. Appl Soft Comput 52(2017):1154–1168
Chutia R (2017) Ranking of fuzzy numbers by using value and angle in the epsilon-deviation degree method. Appl Soft Comput 60(2017):706–721
Dubois D, Prade H (1980) Fuzzy Sets Syst. Theory and Applications. Academic Press. Inc., New York
Hejazi SR, Doostparast A, Hosseini SM (2011) An improved fuzzy risk analysis based on new similarity measures of generalized fuzzy numbers. Expert Syst Applic 38:9179–9185
Nasseri SH, Zadeh MM, Kardoost M, Behmanesh E (2013) Ranking fuzzy quantities based on the angle of the reference functions. Appl Math Modell 37(22):9230–9241
Patra K, Mondal SK (2012) Risk analysis in diabetes prediction based on a new approach of ranking of generalized trapezoidal fuzzy numbers. Cybernetics Syst Int J 43(8):623–650
Patra K, Mondal SK (2014) Fuzzy Risk Analysis of any disaster level using trapezoidal fuzzy number. South Asian J Math 4(1):2014
Patra K, Mondal SK (2015) Multi-Item Supplier Selection Model with Fuzzy Risk Analysis Studied by Possibility and Necessity Constraints. Fuzzy Inform Eng 7(2015):451–474
Patra K, Mondal SK (2015) Fuzzy risk analysis using area and height based similarity measure on generalized trapezoidal fuzzy numbers and its application. Appl Soft Comput 28(2015):276–284
Patra K (2017) Mondal SK (2017) Risk analysis in a production system using fuzzy cognitive map. Int J Math Oper Res 11(1):29–44
Rezvani S (2015) Ranking generalized exponential trapezoidal fuzzy numbers based on variance. Appl Math Computat 262(2015):191–198
Schmucker KJ (1984) Fuzzy Sets, natural language computations, and risk analysis. Computer Science Press, Rockville
Wang CY, Chen SM (2017) Multiple attribute decision making based on interval-valued intuitionistic fuzzy sets, linear programming methodology, and the extended TOPSIS method. Inform Sci 397(2017):155–167
Wang YM, Yang JB, Xu DL, Chin KS (2006) On the centroids of fuzzy numbers. Fuzzy Sets Syst 157(7):919–926
Wei SH, Chen SM (2009) A new approch for fuzzy risk analysis based on similarity measures of generalized fuzzy numbers. Expert Syst Appl 36(1):589–598
Xu Z, Shang S, Quin W, Shu W (2010) A method for fuzzy risk analysis based on the new similarity of trapezoidal fuzzy numbers. Expert Syst Appl 37:1920–1927
Yager RR, (1978) Ranking fuzzy subsets over the unit interval, In 1978 IEEE Conference on Decision and Control including the 17th Symposium on Adaptive Processes, pp. 1435-1437
Yu VF, Chi HTX, Shen CW (2013) Ranking fuzzy numbers based on epsilon-deviation degree. Appl Soft Comput 13(8):3621–3627
Yu VF, Dat LQ (2014) An improved ranking method for fuzzy numbers with integral values, Appl Soft Comput 14(Part C) (2014) 603–608
Zadeh LA (1965) Fuzzy Sets. Inform Control 8:338–356
Zeng S, Chen SM, Kuo LW (2019) Multiattribute decision making based on novel score function of intuitionistic fuzzy values and modified VIKOR method. Inform Sci 488:76–92