Design of Ricker Wavelet Neural Networks for Heat and Mass Transport in Magnetohydrodynamic Williamson Nanofluid Boundary-Layer Porous Medium Flow with Multiple Slips

Design of Ricker Wavelet Neural Networks for Heat and Mass Transport in Magnetohydrodynamic Williamson Nanofluid Boundary-Layer Porous Medium Flow with Multiple Slips

In the current paper, an analysis of magnetohydrodynamic Williamson nanofluid boundary layer flow is presented, with multiple slips in a porous medium, using a newly designed human-brain-inspired Ricker wavelet neural network solver. The solver employs a hybrid approach that combines genetic algorit...

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Bibliographic Details
Main Authors: Zeeshan Ikram Butt, Muhammad Asif Zahoor Raja, Iftikhar Ahmad, Muhammad Shoaib, Rajesh Kumar, Syed Ibrar Hussain
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Magnetochemistry
Subjects:
Ricker wavelet neural networks
Williamson nanofluid
magnetohydrodynamic
genetic algorithms
Online Access:https://www.mdpi.com/2312-7481/11/5/40
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