Predicting Water-Based Nanofluid Viscosity Using Machine Learning: Performance Evaluation of LS-SVM, GMDH, and GP Models

Viscosity is one of the most important properties of nanofluids, which has a direct influence on fluid flow as well as convective heat transfer. Despite extensive experimental studies and theoretical models, accurate prediction of nanofluid viscosity remains challenging due to the complex interplay...

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Библиографические подробности

Главные авторы:	Hassan Abedini, Alexei Rozhenko, Fahimeh Hadavimoghaddam, Mohsen Tamtaji, Jafar Abdi
Формат:	Artigo
Язык:	Inglês
Опубликовано:	Iranian Institute of Research and Development in Chemical Industries (IRDCI)-ACECR 2025-09-01
Серии:	Iranian Journal of Chemistry & Chemical Engineering
Предметы:	least squares support vector machine nanofluids viscosity genetic programming machine learning
Online-ссылка:	https://ijcce.ac.ir/article_727060_06a4a7f31a6018c31736934196261884.pdf
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