VAGUE DECISION MAKING BASED ON ROUGH SETS

Author(s):  
LIN FENG ◽  
TIANRUI LI
Keyword(s):  
2019 ◽  
Vol 14 (1) ◽  
pp. 101-113 ◽  
Author(s):  
Azmat Hussain ◽  
Muhammad Irfan Ali ◽  
Tahir Mahmood
Keyword(s):  

2019 ◽  
Vol 23 (20) ◽  
pp. 9853-9868 ◽  
Author(s):  
Muhammad Akram ◽  
Ghous Ali ◽  
José Carlos R. Alcantud

Symmetry ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 462 ◽  
Author(s):  
Jingqian Wang ◽  
Xiaohong Zhang

Intuitionistic fuzzy rough sets are constructed by combining intuitionistic fuzzy sets with rough sets. Recently, Huang et al. proposed the definition of an intuitionistic fuzzy (IF) β -covering and an IF covering rough set model. In this paper, some properties of IF β -covering approximation spaces and the IF covering rough set model are investigated further. Moreover, we present a novel methodology to the problem of multiple criteria group decision making. Firstly, some new notions and properties of IF β -covering approximation spaces are proposed. Secondly, we study the characterizations of Huang et al.’s IF covering rough set model and present a new IF covering rough set model for crisp sets in an IF environment. The relationships between these two IF covering rough set models and some other rough set models are investigated. Finally, based on the IF covering rough set model, Huang et al. also defined an optimistic multi-granulation IF rough set model. We present a novel method to multiple criteria group decision making problems under the optimistic multi-granulation IF rough set model.


2014 ◽  
Vol 602-605 ◽  
pp. 3379-3383
Author(s):  
Yong Sheng Liu ◽  
Zan Zhang

In multiattribute decision making, it is critical to indentify the importance degree of attributes before the overall assessment of the alternatives. In this paper, we give a measurement of importance degree of attributes based on knowledge discovery in the decision information system, which satisfies the conditions of fuzzy measure. Further, we construct an evaluation model combined Choquet integral with the importance degree measure. The case study illustrates the validity and the effectiveness of the method.


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