ArticleJournal of ambient intelligence and humanized computing2022
An extended MABAC method based on prospect theory with unknown weight information under Fermatean fuzzy environment for risk investment assessment in B&R.
Article in Journal of ambient intelligence and humanized computing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed.
- Effects of maximum and minimum offers on reciprocity and trust perceptions during economic decision-making.Frontiers in cognition · 2025Article
- Article
- A novel perspective on the selection of an effective approach to reduce road traffic accidents under Fermatean fuzzy settings.PloS one · 2024Article
- Article
- Selecting the foremost big data tool to optimize YouTube data in dynamic Fermatean fuzzy knowledge.PloS one · 2024Article
- Enhancing breast cancer treatment selection through 2TLIVFrontiers in artificial intelligence · 2024Article
- Optimal Design of Wood/Rice Husk-Waste-Filled PLA Biocomposites Using Integrated CRITIC-MABAC-Based Decision-Making Algorithm.Polymers · 2022Article
- Fermatean fuzzy set extensions of SAW, ARAS, and VIKOR with applications in COVID-19 testing laboratory selection problem.Expert systems · 2021Article
- Multi-criteria healthcare waste disposal location selection based on Fermatean fuzzy WASPAS method.Complex & intelligent systems · 2021Article
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5 authors.
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Abstract
The assessment of investment risk for the countries along the route in Belt and Road (B&R) can be deemed as a multiple criteria group decision making (MCGDM) issue since multiple investment options based on diverse criterions are assessment by experts. Pondering that the complexity and uncertainty of the assessment setting and the cognition fuzziness and psychological behavior of experts bring challenges to risk assessment, this paper designed an integrated MCGDM risk investment evaluation framework by synthesizing MABAC method and prospect theory under Fermatean fuzzy setting. Firstly, a Fermatean fuzzy interactive distance measure is presented to ascertain the weight of evaluation experts and criterions. Next, some Fermatean fuzzy Frank aggregation operators based upon the proposed Frank operations are developed to fuse Fermatean fuzzy information efficiently. In addition, an innovative evaluation framework for risk investment is designed based on improved prospect theory MABAC and CRITIC approaches. Conclusively, an empirical concerning risk investment issues in B&R is employed to confirm the applicability and feasibility of the constructed evaluation framework, involving the simulation experiments on sensitivity analysis and contrast studies. The assessment information provided by investors using the linguistic assessment terms based upon their cognition ability of them. These outcomes obtained by the propounded method and comparison analysis further emphasize the validity and salient merits of the propounded framework and provide several auxiliary suggestions for investors.
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