https://doi.org/10.1140/epjs/s11734-022-00608-4
Regular Article
Application of long short-term memory neural network and optimal control to variable-order fractional model of HIV/AIDS
1
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
Received:
4
August
2021
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 original online version of this article was revised to remove Amirreza Yasami as corresponding author.
A correction to this article is available online at https://doi.org/10.1140/epjs/s11734-022-00623-5.
Copyright comment corrected publication 2022
© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2022. corrected publication 2022
