A Distance-Based Parameter Reduction Algorithm of Fuzzy Soft Sets

Kong et al. introduced the concept of normal parameter reduction in fuzzy soft sets. However, due to entries of fuzzy soft sets belonging to the unit interval [0, 1], it is nearly impossible to obtain the normal parameter reduction of fuzzy soft sets in the real applications. At the same time, this...

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Bibliographic Details
Published in:IEEE access 2018-01, Vol.6, p.10530-10539
Main Authors: Ma, Xiuqin, Qin, Hongwu
Format: Article
Language:English
Subjects:
Algorithms
Computation
Decision making
distance
Fuzzy sets
Fuzzy soft sets
Mathematical model
parameter reduction
Parameters
Reduction
Rough sets
Uncertainty
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Summary:Kong et al. introduced the concept of normal parameter reduction in fuzzy soft sets. However, due to entries of fuzzy soft sets belonging to the unit interval [0, 1], it is nearly impossible to obtain the normal parameter reduction of fuzzy soft sets in the real applications. At the same time, this method involves a great amount of computation. In order to solve these problems, in this paper, we propose a distance-based parameter reduction of fuzzy soft set, which has much higher applicability and involves much less computation compared with the method of normal parameter reduction of fuzzy soft sets. Two case studies and twenty synthetic generated datasets show our contributions.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2018.2800017