Numerical Treatment of Non-Linear System for Latently Infected CD4+T Cells: A Swarm- Optimized Neural Network Approach-Reference-Cited by-同舟云学术

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

Published:2024 Issue: Volume:12 Page:103119-103132
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Riaz Farhad Muhammad¹^ORCID,Ahmad Shafiq²^ORCID,Khan Juniad Ali¹^ORCID,Altaf Saud³^ORCID,Rehman Zia Ur⁴^ORCID,Memon Shuaib Karim⁵

Affiliation:

1. Department of Computer Science, HITEC University, Taxila, Pakistan

2. Industrial Engineering Department, College of Engineering, King Saud University, Riyadh, Saudi Arabia

3. Department of Information Engineering Technology, National Skills University Islamabad, Islamabad, Pakistan

4. Department of Computer Science, National University of Modern Languages (NUML), Islamabad, Pakistan

5. Department of Computer Science, York St John University, York, U.K.

Funder

King Saud University, Riyadh, Saudi Arabia, through the Researchers Supporting

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10599415.pdf?arnumber=10599415

Reference58 articles.

1. Dynamics of HIV infection of CD4+ T cells

2. Asymptotic behavior of HIV-1 epidemic model with infinite distributed intracellular delays

3. Artificial neural networks for solving ordinary and partial differential equations

4. An Introduction to Neural Network Methods for Differential Equations

5. Robust Semantic Segmentation With Multi-Teacher Knowledge Distillation

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