Comment on "Fuzzy Soft Sets” [The Journal of Fuzzy Mathematics, 9(3), 2001, 589–602]
Citation: Enginoğlu, S., Memiş, S., 2018. Comment on "Fuzzy Soft Sets” [The Journal of Fuzzy Mathematics, 9(3), 2001, 589–602]. International Journal of Latest Engineering Research and Applications, 3(9), 1-9. link: http://www.ijlera.com/papers/v3-i9/1.201809134.pdf
Abstract:
The concept of fuzzy soft sets was defined and applied to a decision-making problem by Maji et al. in 2001. The decision-making method used therein has potential for applications in several areas such as machine learning and image processing. Recently, this method has been configured by Enginoğlu and Memiş via fuzzy parameterized fuzzy soft matrices (fpfs-matrices), faithfully to the original, because a more general form is needed for the method in the event that the parameters have uncertainties. However, in the case that a large amount of data is processed, the configured method denoted by MBR01 has a disadvantage concerning time and complexity. To deal with this problem and to be able to use this method effectively, we propose an algorithm in this paper, i.e. sMBR01, and prove that sMBR01 is equivalent to MBR01. We then compare the running times of these two algorithms. The results show that sMBR01 is more successful than the other in any number of data. Especially while a large number of objects are processed, sMBR01 offers up to 82.9602% of time advantage and while a large number of parameters are processed, sMBR01 offers up to 79.1337%. Afterwards, we apply this method to a performance-based value assignment to some filters used in noise removal, so that we can order them in terms of performance. Finally, we discuss the need for further research.