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An Intelligent Similarity Model between Generalized Trapezoidal Fuzzy Numbers in Large Scale
Int. J. Fuzzy Log. Intell. Syst. 2018;18(4):303-315
Published online December 25, 2018
© 2018 Korean Institute of Intelligent Systems.

Mohamedou Cheikh Tourad and Abdelmounaim Abdali

Applied Mathematics and Computer Science Laboratory, Cadi Ayyad University, Marrakech, Morocco
Correspondence to: Mohamedou Cheikh Tourad (cheikhtouradmohamedou@gmail.com)
Received November 13, 2018; Revised December 19, 2018; Accepted December 24, 2018.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
The rapid expansion of data published on the web has given rise to the similarity problem on a large scale, a very important subject for scientific research in the field of computer science. Several methods have been developed for this. In this paper, we propose the first mathematical model to find the similarity value between generalized trapezoidal fuzzy numbers (GTFNs). This model employs fuzzy inference systems to find the value of an effective weighting, the weights to be associated to different kinds of methods that can handle an important scale of the data. This model will allow us to develop intelligent systems. A comparative study based on 21 sets of GTFNs has been carried out to demonstrate the difference between our approach and existing methods. This study shows that our model is more reasonable than existing methods.
Keywords : Cosine coefficient, Jaccard index, GTFNs, FIS, Similarity, Large scale