Radial basis kernel harmony in neural networks for the analysis of MHD Williamson nanofluid flow with thermal radiation and chemical reaction: An evolutionary approach

Radial basis kernel harmony in neural networks for the analysis of MHD Williamson nanofluid flow with thermal radiation and chemical reaction: An evolutionary approach

The current investigative exploration exemplifies the conceptualization of a novel design intelligent computing paradigm based on artificial neural networks (ANNs) by utilizing radial basis function (RBF) to analyze magnetohydrodynamic (MHD) Williamson nanofluid two-dimensional flow along a stretcha...

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Bibliographic Details
Main Authors: Zeeshan Ikram Butt, Muhammad Asif Zahoor Raja, Iftikhar Ahmad, Syed Ibrar Hussain, Muhammad Shoaib, Hira Ilyas
Format: Article
Language:English
Published: Elsevier 2024-09-01
Series:Alexandria Engineering Journal
Subjects:
Radial basis function
Williamson nanofluid
Inverse multiquadric
Chemical reaction
Artificial Intelligence
Sequential quadratic programming
Online Access:http://www.sciencedirect.com/science/article/pii/S1110016824006082

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http://www.sciencedirect.com/science/article/pii/S1110016824006082

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