Soft Computing Paradigms to Find the Numerical Solutions of a Nonlinear Influenza Disease Model

Applied Sciences

Muhammad Umar¹  Zulqurnain Sabir¹  Ag Asri Ag Ibrahim²  Kashif Nisar²  Muhammad Asif Zahoor Raja³  Samy R. Mahmoud⁴  Joel J. P. C. Rodrigues⁵ 

[1] Department of Mathematics and Statistics, Hazara University, Mansehra 21300, Pakistan;Faculty of Computing and Informatics, Universiti Malaysia Sabah, Jalan UMS, Kota Kinabalu 88400, Sabah, Malaysia;Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou 64002, Yunlin, Taiwan;GRC Department, Faculty of Applied Studies, King Abdulaziz University, Jeddah 21589, Saudi Arabia;Post-Graduation Program in Electrical Engineering, Federal University of Piauí (UFPI), Teresina 64049-550, Brazil;

关键词: influenza disease system;    Adams methods;    artificial neural networks;    active-set method;    genetic algorithms;    statistical performances;   

DOI  :  10.3390/app11188549

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown