Open Access

ARTICLE

New Trends in Fuzzy Modeling Through Numerical Techniques

M. M. Alqarni¹, Muhammad Rafiq², Fazal Dayan^3,*, Jan Awrejcewicz⁴, Nauman Ahmed⁵, Ali Raza⁶, Muhammad Ozair Ahmad⁵, Witold Pawłowski⁷, Emad E. Mahmoud⁸

1 Department of Mathematics, College of Sciences, King Khalid University, Abha, 61413, Saudi Arabia
2 Department of Mathematics, Faculty of Sciences and Technology, University of Central Punjab, Lahore, Pakistan
3 Department of Mathematics, School of Science, University of Management and Technology, Lahore, Pakistan
4 Department of Automation, Biomechanics and Mechatronics, Lodz University of Technology, 1/15 Stefanowskiego St., 90-924, Lodz, Poland
5 Department of Mathematics and Statistics, University of Lahore, Lahore, Pakistan
6 Department of Mathematics, Govt. Maulana Zafar Ali Khan Graduate College Wazirabad, Punjab Higher Education Department (PHED), Lahore, 54000, Pakistan
7 Institute of Machine Tools and Production Engineering, Lodz University of Technology, Poland
8 Department of Mathematics, College of Science, Taif University, P. O. Box, 11099, Taif, 21944, Saudi Arabia

* Corresponding Author: Fazal Dayan. Email:

Computers, Materials & Continua 2023, 74(3), 6371-6388. https://doi.org/10.32604/cmc.2023.033553

Received 20 June 2022; Accepted 02 September 2022; Issue published 28 December 2022

Abstract

Amoebiasis is a parasitic intestinal infection caused by the highly pathogenic amoeba Entamoeba histolytica. It is spread through person-to-person contact or by eating or drinking food or water contaminated with feces. Its transmission rate depends on the number of cysts present in the environment. The traditional models assumed a homogeneous and contradictory transmission with reality. The heterogeneity of its transmission rate is a significant factor when modeling disease dynamics. The heterogeneity of disease transmission can be described mathematically by introducing fuzzy theory. In this context, a fuzzy SEIR Amoebiasis disease model is considered in this study. The equilibrium analysis and reproductive number are studied with fuzziness. Two numerical schemes forward Euler method and a nonstandard finite difference (NSFD) approach, are developed for the learned model, and the results of numerical simulations are presented. The numerical and simulation results reveal that the proposed NSFD method provides an adequate representation of the dynamics of the disease despite the uncertainty and heterogeneity. Moreover, the obtained method generates plausible predictions that regulators can use to support decision-making to design and develop control strategies.

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Keywords

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