Investment decision making in the fuzzy context: An integrated model approach

被引:1
|
作者
Zhang, Shasha [1 ]
Liu, Xiaodi [1 ]
Garg, Harish [2 ,3 ,4 ]
Zhang, Shitao [1 ]
机构
[1] Anhui Univ Technol, Sch Math & Phys, Maanshan 243002, Anhui, Peoples R China
[2] Thapar Inst Engn & Technol Deemed Univ, Sch Math, Patiala, Punjab, India
[3] Graph Era Deemed Univ, Dept Math, Dehra Dun, Uttarakhand, India
[4] Appl Sci Private Univ, Appl Sci Res Ctr, Amman, Jordan
基金
中国国家自然科学基金;
关键词
Investment decision making; Distance; Correlation coefficient; Disappointment theory; Probabilistic hesitant fuzzy sets; REGRET THEORY; PROSPECT-THEORY; DISAPPOINTMENT; CHOICE;
D O I
10.3233/JIFS-223059
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the implementation and steady progress of the Belt and Road (B&R) initiative, China's investment in countries along the B&R has maintained a high growth trend. Generally speaking, investment problems are often accompanied by high risk and uncertainty, and howto make the suitable investment decision is a difficult issue. This paper investigates an investment decision approach under the probabilistic hesitant fuzzy environment. Firstly, a new probabilistic hesitant fuzzy distance and correlation coefficient are defined to overcome the defects of the existing probabilistic hesitant fuzzy information measures. Secondly, an attribute weight integrated model is constructed by combining the maximum deviation method, the CRITIC method and the maximum entropy principle, which is able to take into account the correlation between attributes and make full use of the decision information. In addition, a disappointment theory-based probabilistic hesitant fuzzy multi-attribute decision making (PHFMADM) method is proposed to solve the investment decision problem, which can integrate the psychological behavior of decision makers into the decision making process and make the decision results more authentic and reliable. Finally, the rationality and validity of the method are verified by comparing with the existing methods.
引用
收藏
页码:3763 / 3786
页数:24
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