Muhammad Umar¹, Fazli Amin¹, Soheil Salahshour², Thongchai Botmart³, Wajaree Weera³, Prem Junswang^4,*, Zulqurnain Sabir¹

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6185-6202, 2022, DOI:10.32604/cmc.2022.027970 - 21 April 2022

Abstract The present study is related to design a stochastic framework for the numerical treatment of the Van der Pol heartbeat model (VP-HBM) using the feedforward artificial neural networks (ANNs) under the optimization of particle swarm optimization (PSO) hybridized with the active-set algorithm (ASA), i.e., ANNs-PSO-ASA. The global search PSO scheme and local refinement of ASA are used as an optimization procedure in this study. An error-based merit function is defined using the differential VP-HBM form as well as the initial conditions. The optimization of the merit function is accomplished using the hybrid computing performances of More >

Zulqurnain Sabir¹, Muhammad Umar¹, Muhammad Asif Zahoor Raja^2,*, Dumitru Baleanu^3,4

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 227-251, 2021, DOI:10.32604/cmes.2021.016611 - 24 August 2021

Abstract The presented research aims to design a new prevention class (P) in the HIV nonlinear system, i.e., the HIPV model. Then numerical treatment of the newly formulated HIPV model is portrayed handled by using the strength of stochastic procedure based numerical computing schemes exploiting the artificial neural networks (ANNs) modeling legacy together with the optimization competence of the hybrid of global and local search schemes via genetic algorithms (GAs) and active-set approach (ASA), i.e., GA-ASA. The optimization performances through GA-ASA are accessed by presenting an error-based fitness function designed for all the classes of the More >