Version 1
: Received: 26 October 2024 / Approved: 28 October 2024 / Online: 29 October 2024 (10:41:04 CET)
How to cite:
Gulzar, M.; Ashraf, S.; Kerre, A. E. E. Application of Complex Fuzzy Relational Compositions to Medical Diagnosis. Preprints2024, 2024102243. https://doi.org/10.20944/preprints202410.2243.v1
Gulzar, M.; Ashraf, S.; Kerre, A. E. E. Application of Complex Fuzzy Relational Compositions to Medical Diagnosis. Preprints 2024, 2024102243. https://doi.org/10.20944/preprints202410.2243.v1
Gulzar, M.; Ashraf, S.; Kerre, A. E. E. Application of Complex Fuzzy Relational Compositions to Medical Diagnosis. Preprints2024, 2024102243. https://doi.org/10.20944/preprints202410.2243.v1
APA Style
Gulzar, M., Ashraf, S., & Kerre, A. E. E. (2024). Application of Complex Fuzzy Relational Compositions to Medical Diagnosis. Preprints. https://doi.org/10.20944/preprints202410.2243.v1
Chicago/Turabian Style
Gulzar, M., Samina Ashraf and And Etienne E Kerre. 2024 "Application of Complex Fuzzy Relational Compositions to Medical Diagnosis" Preprints. https://doi.org/10.20944/preprints202410.2243.v1
Abstract
The capability of the complex fuzzy sets plays a valuable role to resolve many real life problems. In this paper, we present the compositions of complex fuzzy relations by using the idea of implication operators and max-product compositions of complex fuzzy relations and illustrate these compositions with concrete examples. The converse of these newly invented triangular compositions in terms of compositions of the converse relations are also defined. We also study the interactions with union and intersection. The main goal of this article to present a new technique to enhance medical diagnostic model that can assist to increase the features of healthcare systems. We utilize these compositions to determine the diseases of patients on the basis of intensity of symptoms.
Computer Science and Mathematics, Applied Mathematics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
