Numerical Treatment of Non-Linear System for Latently Infected CD4+T Cells: A Swarm- Optimized Neural Network Approach

Swarm-inspired computing techniques are the best candidates for solving various nonlinear problems. The current study aims to exploit the swarm intelligence technique known as Particle Swarm Optimization (PSO) for the numerical investigation of a nonlinear system of latently infected CD4+T cells. Th...

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Bibliografiset tiedot

Päätekijät:	Farhad Muhammad Riaz, Shafiq Ahmad, Juniad Ali Khan, Saud Altaf, Zia Ur Rehman, Shuaib Karim Memon
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	IEEE 2024-01-01
Sarja:	IEEE Access
Aiheet:	Mathematical modeling artificial neural network hybrid optimization nonlinear system of latently infected CD4+ T cells Monte Carlo simulations ANN-based numerical treatment
Linkit:	https://ieeexplore.ieee.org/document/10599415/
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