Soft computing paradigms to find the numerical solutions of a nonlinear influenza disease model

Zulqurnain Sabir and Ag. Asri Ag. Ibrahim and Muhammad Asif Zahoor Raja and Kashif Nisar and Muhammad Umar and Joel J. P. C. Rodrigues and Samy R. Mahmoud (2021) Soft computing paradigms to find the numerical solutions of a nonlinear influenza disease model. Applied Sciences (Switzerland), 11. pp. 1-16. ISSN 2076-3417

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Abstract

The aim of this work is to present the numerical results of the influenza disease nonlinear system using the feed forward artificial neural networks (ANNs) along with the optimization of the combination of global and local search schemes. The genetic algorithm (GA) and active-set method (ASM), i.e., GA-ASM, are implemented as global and local search schemes. The mathematical nonlinear influenza disease system is dependent of four classes, susceptible S(u), infected I(u), recovered R(u) and cross-immune individuals C(u). For the solutions of these classes based on influenza disease system, the design of an objective function is presented using these differential system equations and its corresponding initial conditions. The optimization of this objective function is using the hybrid computing combination of GA-ASM for solving all classes of the influenza disease nonlinear system. The obtained numerical results will be compared by the Adams numerical results to check the authenticity of the designed ANN-GA-ASM. In addition, the designed approach through statistical based operators shows the consistency and stability for solving the influenza disease nonlinear system.

Item Type:	Article
Keyword:	Influenza disease system , Adams methods , Artificial neural networks , Active-set method , Genetic algorithms , Statistical performances
Subjects:	Q Science > QA Mathematics > QA1-939 Mathematics > QA71-90 Instruments and machines
Department:	FACULTY > Faculty of Computing and Informatics
Depositing User:	SAFRUDIN BIN DARUN -
Date Deposited:	19 May 2022 09:26
Last Modified:	19 May 2022 09:26
URI:	https://eprints.ums.edu.my/id/eprint/32623

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