| Yazarlar |
Muhammad Umar
|
|
Sabir Zulqurnain
|
|
Muhammad Asif Zahoor Raja
|
|
Hacı Mehmet Başkonuş
Harran Üniversitesi, Türkiye |
|
Yaod Shao-Wen
|
Doç. Dr. Esin İLHAN
Kırşehir Ahi Evran Üniversitesi, Türkiye |
| Özet |
| The aim of this study is to provide the numerical outcomes of a nonlinear HIV infection system of latently infected CD4+ T cells exists in bioinformatics using Morlet wavelet (MW) artificial neural networks (ANNs) optimized initially with global search of genetic algorithms (GAs) hybridized for speedy local search of sequential quadratic programming (SQP), i.e., MW-ANN-GA-SQP. The design of an error function is presented by designing the MW-ANN models for the differential equations along with the initial conditions that represent the HIV infection system involving latently infected CD4+ T cells. The precision and persistence of the presented approach MW-ANN-GA-SQP are recognized through comparative studies from the results of the Runge-Kutta numerical scheme for solving the HIV infection spread system in case of single and multiple trails of the MW-ANN-GA-SQP. Statistical estimates with 'Theil's inequality coefficient' and 'root mean square error' based indices further validate the sustainability and applicability of proposed MW-ANN-GA-SQP solver. |
| Anahtar Kelimeler |
| Morlet wavelets | HIV infection models | Genetic algorithms | Neural networks | Sequential quadratic programming | Bioinformatics |
| Makale Türü | Özgün Makale |
| Makale Alt Türü | SSCI, AHCI, SCI, SCI-Exp dergilerinde yayımlanan tam makale |
| Dergi Adı | RESULTS IN PHYSICS |
| Dergi ISSN | 2211-3797 |
| Dergi Tarandığı Indeksler | SCI-Expanded |
| Dergi Grubu | Q1 |
| Makale Dili | İngilizce |
| Basım Tarihi | 06-2021 |
| Cilt No | 25 |
| Sayfalar | 1 / 13 |
| Doi Numarası | 10.1016/j.rinp.2021.104235 |
| Makale Linki | http://dx.doi.org/10.1016/j.rinp.2021.104235 |
| Atıf Sayıları | |
| WoS | 64 |
| Google Scholar | 73 |
