Computational intelligence of Bayesian regularization backpropagation neural networks to study the thermo-bioconvection flow of hybrid-nanofluid with thermal Radiation: Biotechnological perspectives

This study aims to develop a deep neural network that utilizes Bayesian regularization to investigate the performance of gyrotactic and oxytactic microbes in hybrid nanofluid flow over a sheet, taking into account local thermal non-equilibrium effects and thermal radiation. Two different activation...

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Veröffentlicht in:	Journal of Radiation Research and Applied Sciences Jg. 18; H. 3; S. 101777
Hauptverfasser:	Abbas, Munawar, Medani, Mohamed, Rajab, Adnan Burhan, Elaissi, Samira, Zayani, Hafedh Mahmoud, Faiz, Zeshan, Khan, Ilyas, Ben Khedher, Nidhal
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.09.2025
Schlagworte:	Bayesian regularization algorithm Hybrid nanofluid Local thermal non-equilibrium conditions Oxytactic and gyrotactic microbe Thermophoretic particle deposition Oxytactic and gyrotactic microbe Thermophoretic particle deposition Bayesian regularization algorithm Local thermal non-equilibrium conditions Hybrid nanofluid
ISSN:	1687-8507
Online-Zugang:	Volltext
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