Paper Info
Title
Some novel decision making algorithms for intuitionistic fuzzy soft set.
Abstract
This paper is designed to show deeper standpoints for dealing the decision making issues based on intuitionistic fuzzy soft set (IFSS). Firstly, we propose a novel definition and formula of similarity measure on intuitionistic fuzzy information, which can reserve more original judgment information. Afterwards, we present a combination weight that take the objective weight (obtained by grey system theory) and the subjective weight into consideration. Later, three intuitionistic fuzzy soft methods based on similarity measure, MABAC and EDAS are presented for dealing the decision making issues. Finally, the validity of methods are stated by some practical examples. The key characteristics of the developed methods have no strict requirements for decision data and possess a stronger ability in differentiating the best alternative.
Year
DOI
Venue
2019
10.3233/JIFS-182768
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
Keywords
Field
DocType
Similarity measure,combination weights,IFSS,MABAC,EDAS
Artificial intelligence,Fuzzy soft set,Machine learning,Mathematics
Journal
Volume
Issue
ISSN
37
1
1064-1246
Citations 
PageRank 
References 
0
0.34
0
Authors
1
Name
Order
Citations
PageRank
Xindong Peng1287.11