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 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.