Linguistic-Valued Lattice Implication Algebra TOPSIS Method Based on Entropy Weight Method

被引：0
|
作者：
Wang, Hongdong [1 ]
Meng, Jia [1 ]
Zou, Li [1 ]
Luo, Siyuan [2 ]
Shi, Yuanyuan [2 ]
机构：
[1] Liaoning Normal Univ, Sch Comp & Informat Technol, Dalian, Peoples R China
[2] Liaoning Normal Univ, Sch Math, Dalian, Peoples R China
来源：
2017 12TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND KNOWLEDGE ENGINEERING (IEEE ISKE) | 2017年
关键词：
linguistic valued implication algebra; L-V(nx2) distance; entropy weight method; TOPSIS; L-V(nx2) similarity; INTUITIONISTIC FUZZY-SETS; DECISION-MAKING;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In order to solve the multi-attribute group decision making problems,which the attribute weight is unknown and the index value of the alternative is linguistic-valued lattice implication algebra(L-V(nx2)). This paper proposes a linguistic valued lattice implication algebra TOPSIS method based on entropy weight method. We study the distance between the linguistic-valued on L-V(nx2) and their properties. Based to L-V(nx2) puts forward the Euclidean distance and weighted Euclidean distance get the similarity between the linguistic-valued on L-V(nx2). The weight of the attributes are determined according to the L-V(nx2) entropy method, and the alternatives are compared and ordered by TOPSIS method. The feasibility and validity of the method are verified by case analysis.
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页数：8
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