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New Improved Normal Parameter Reduction Method for Fuzzy Soft Set
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DOI：10.1109/ACCESS.2019.2949142.png)
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Abstract
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There are many redundant parameters in the actual decision-making process based on fuzzy soft sets. Kong et al. [Z. Kong, J. Ai, L. Wang, P. Li, L. Ma, and F. Lu, New Normal Parameter Reduction Method in Fuzzy Soft Set Theory,'' in IEEE Access, vol. 7, pp. 2986-2998, 2019] described the parameter reduction method with regard to four special dispensable sets based on score decision criteria. However, this method is complicated and has high computational complexity. This paper firstly gives some new calculation methods of comparison matrix, and then proposes a new improved normal parameter reduction method. The comparison results on two real-life datasets validate that the proposed algorithm reduces the complexity of the algorithm and greatly simplifies the process of parameter reduction compared with the algorithm of Kong et al.
Keywords:
Fuzzy soft sets
score decision criteria
dispensable sets
parameter reduction
decision making
Journal
IF:
3.6
Papers:
9.8W
Citations:
29.4W