Grey Relational Method for Evaluating the Macro-Economy Performance with Triangular Fuzzy Information

2016 ◽  
Vol 13 (10) ◽  
pp. 7385-7389
Author(s):  
Xian-Ling Jiang ◽  
Yi-Lin Zhao

The new theory comes when the current economic circumstance cannot be explained. The Great Depression in 1930s severely smashed the world economy and no explanations and policies were provided by the classical laissez-faire until the Roosevelt New Deal took the world economy out of depression. The macroeconomic theory has been brought out by John Maynard Keynes. Early this century, not only did the US Sub-prime crisis strongly affect the world economy, but also the macroeconomic theory. The development of the macroeconomic theory after the Sub-prime crisis becomes a hot topic. In this paper, we investigate the multiple attribute decision making (MADM) problems for evaluating the macro-economy performance with triangular fuzzy information. Then, we extend the grey relational analysis (GRA) procedure for triangular fuzzy multiple attribute decision making for evaluating the macro-economy performance in triangular fuzzy setting. According to the concept of the GRA, a fuzzy relative relational degree is defined to determine the ranking order of all alternatives by calculating the degree of fuzzy grey relational coefficient to both the triangular fuzzy positive-ideal solution (TFPIS) and triangular fuzzy negative-ideal solution (TFNIS) simultaneously. Finally, an illustrative example for evaluating the macro-economy performance is given to verify the developed approach and to demonstrate its practicality and effectiveness.

2016 ◽  
Vol 13 (10) ◽  
pp. 7333-7335
Author(s):  
Yanying Ma ◽  
Xue Wang ◽  
Jizhang Fan

With the rapid economic development, China is facing a comparatively short supply of mineral resources after the relatively long-term developmental stage that is based on the consumption of mineral resources. Contradictions among the population, resources, the environment and developments have arisen. Therefore, under the constraint conditions of limited and non-renewable mineral resources, the mineral resources industry in China must adhere to sustainable development. The aim of this paper is to investigate the multiple attribute decision making problems for quantitative prediction of mineral resources with dual hesitant fuzzy information and incomplete weight information. Then, based on the traditional GRA method, calculation steps for solving dual hesitant fuzzy multiple attribute decision-making problems with incomplete weight information are proposed. Finally, an algorithm of quantitative prediction of mineral resources based on the grey relational analysis with dual hesitant fuzzy information is proposed.


2014 ◽  
Vol 2014 ◽  
pp. 1-4 ◽  
Author(s):  
Ming Xue

We investigate the multiple attribute decision-making problems for evaluating the computer network security with intuitionistic trapezoidal fuzzy information. We utilize the intuitionistic trapezoidal fuzzy weighted average (ITFWA) operator to aggregate the intuitionistic trapezoidal fuzzy information corresponding to each alternative and get the overall value of the alternatives and then rank the alternatives and select the most desirable one(s) according to the distance between the overall value of the alternatives and ideal solution. Finally, an illustrative example for evaluating the computer network security is given.


2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Wei Yang ◽  
Jiarong Shi ◽  
Yongfeng Pang

Some hybrid aggregation operators have been developed based on linguistic hesitant intuitionistic fuzzy information. The generalized linguistic hesitant intuitionistic fuzzy hybrid weighted averaging (GLHIFHWA) operator and the generalized linguistic hesitant intuitionistic fuzzy hybrid geometric mean (GLHIFHGM) operator are defined. Some special cases of the new aggregation operators are studied and many existing aggregation operators are special cases of the new operators. A new multiple attribute decision making method based on the new aggregation operators is proposed and a practical numerical example is presented to illustrate the feasibility and practical advantages of the new method.


2016 ◽  
Vol 13 (10) ◽  
pp. 7394-7398
Author(s):  
Yi-Ding Zhao ◽  
Zhi-Min Li ◽  
Xi-Guang Zhang

To study the problem of multiple attribute decision making in which the decision making information values are triangular fuzzy number, a relative entropy decision making method for software quality evaluation is proposed. Then, according to the concept of the relative entropy, the relative closeness degree is defined to determine the ranking order of all alternatives by calculating the relative entropy to both the fuzzy positive-ideal solution (FPIS) and fuzzy negative-ideal solution (FNIS) simultaneously. At last, a numerical example for software quality evaluation is provided to illustrate the proposed method. The result shows the approach is simple, effective and easy to calculate.


2016 ◽  
Vol 13 (10) ◽  
pp. 7120-7124
Author(s):  
Hong Jin

In this paper, we investigate the multiple attribute decision making problems about risk evaluation for risk investment projects with triangular intuitionistic fuzzy information. Then, we proposed the triangular intuitionistic fuzzy Einstein weighted geometric (TIFEWG) operator, triangular intuitionistic fuzzy Einstein ordered weighted geometric (TIFEOWG) operator and triangular intuitionistic fuzzy Einstein hybrid geometric (TIFEHG) operator and we develop an approach to multiple attribute decision making with triangular intuitionistic fuzzy information. Finally, an illustrative example for evaluating the risk of the risk investment projects with triangular intuitionistic fuzzy information is given to verify the developed approach.


2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Ju Wu ◽  
Fang Liu ◽  
Yuan Rong ◽  
Yi Liu ◽  
Chengxi Liu

Information fusion is an important part of multiple-attribute decision-making, and aggregation operator is an important tool of decision information fusion. Integration operators in a variety of fuzzy information environments have a slight lack of consideration for the correlation between variables. Archimedean copula provides information fusion patterns that rely on the intrinsic relevance of information. This paper extends the Archimedean copula to the aggregation of hesitant fuzzy information. Firstly, the Archimedean copula is used to generate the operation rules of the hesitant fuzzy elements. Secondly, the hesitant fuzzy copula Bonferroni mean operator and hesitant fuzzy weighted copula Bonferroni mean operator are propounded, and several properties are proved in detail. Furthermore, a decision-making method based on the operators is proposed, and the specific decision steps are given. Finally, an example is presented to illustrate the practical advantages of the method, and the sensitivity analysis of the decision results with the change of parameters is carried out.


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