Support vector machine learning classification of heat transfer rate in tri-hybrid nanofluid over a 3D stretching surface with suction effects for water at 10°C and 50°C

Significance of the present study: Using machine learning and nanofluids for accurate heat transfer analysis, this study helps optimise thermal management systems in sectors such as advanced heat exchangers, biomedical devices, and electronics cooling. Several researchers have expressed interest in...

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Bibliographic Details

Published in:	Alexandria Engineering Journal
Main Authors:	Maddina Dinesh Kumar, C.S.K. Raju, Nehad Ali Shah, Se-Jin Yook, Dharmaiah Gurram
Format:	Article
Language:	English
Published:	Elsevier 2025-04-01
Subjects:	MLR (Multi Linear Regression) analysis Magnetic Suction Support Vector Machine Learning (SVM) Linear Thermal Radiation Non-Fourier flux
Online Access:	http://www.sciencedirect.com/science/article/pii/S1110016825000833