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

• Main Authors: Zulqurnain Sabir, Ag. Asri Ag. Ibrahim, Muhammad Asif Zahoor Raja, Kashif Nisar, Muhammad Umar, Joel J. P. C. Rodrigues, Samy R. Mahmoud
• Format: Article
• Language: English; English
• Published: Multidisciplinary Digital Publishing Institute 2021
• Subjects: QA71-90 Instruments and machines
• Online Access: https://eprints.ums.edu.my/id/eprint/32623/1/Soft%20computing%20paradigms%20to%20find%20the%20numerical%20solutions%20of%20a%20nonlinear%20influenza%20disease%20model.pdf; https://eprints.ums.edu.my/id/eprint/32623/3/Soft%20computing%20paradigms%20to%20find%20the%20numerical%20solutions%20of%20a%20nonlinear%20influenza%20disease%20model%20_ABSTRACT.pdf; https://eprints.ums.edu.my/id/eprint/32623/; https://www.mdpi.com/2076-3417/11/18/8549/htm; https://doi.org/10.3390/app11188549

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.,...