Application of long short-term memory neural network and optimal control to variable-order fractional model of HIV/AIDS
Department of Mechanical Engineering, University of Alberta, AB T6G 1H9, Edmonton, Canada
2 School of Mechatronic Systems Engineering, Simon Fraser University, 250-13450 102 Avenue, V3T 0A3, Surrey, BC, Canada
3 Department of Mechanical and Aerospace Engineering, University of California, 92697, Irvine, CA, USA
Accepted: 25 April 2022
Published online: 31 May 2022
A variable-order fractional model of HIV/AIDS is proposed in this research. Afterward, the equilibrium points are determined, and their stability is investigated. Then, using a new algorithm that uses particle swarm optimization and a long short-term memory neural network, the time-varying derivative of the model is estimated. Next, an optimal control method for the proposed HIV/AIDS model is considered. Finally, through numerical simulations, the excellent performance of the proposed method for identifying the time-varying derivatives and optimal control method were demonstrated, and the result of the simulations depicted.
© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2022. corrected publication 2022