Mathematical and artificial neural network modeling to predict the heat transfer of mixed convective electroosmotic nanofluid flow with Helmholtz-Smoluchowski velocity and multiple slip effects: An application of soft computing

Mathematical and artificial neural network modeling to predict the heat transfer of mixed convective electroosmotic nanofluid flow with Helmholtz-Smoluchowski velocity and multiple slip effects: An application of soft computing

The growing popularity of artificial neural networks (ANNs) is due to their exceptional capability in handling complex and highly nonlinear mathematical problems. ANNs provide a flexible computational framework that is extremely useful in complex fields such as biological computation, fluid dynamics...

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Bibliographic Details
Main Authors: Shan Ali Khan, Umar Farooq, Muhammad Imran, Haihu Liu, Taseer Muhammad, Metib Alghamdi
Format: Article
Language:English
Published: Elsevier 2024-09-01
Series:Case Studies in Thermal Engineering
Subjects:
Artificial neural network
Electroosmosis
Exponential stretching sheet
Helmholtz-Smoluchowski velocity
Multiple slip
Heat source/sink
Online Access:http://www.sciencedirect.com/science/article/pii/S2214157X2400981X

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http://www.sciencedirect.com/science/article/pii/S2214157X2400981X

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