Using of artificial neural networks and different evolutionary algorithms to predict the viscosity and thermal conductivity of silica-alumina-MWCN/water nanofluid

Using of artificial neural networks and different evolutionary algorithms to predict the viscosity and thermal conductivity of silica-alumina-MWCN/water nanofluid

This study predicts the parameters such as viscosity and thermal conductivity in silica-alumina-MWCN/water nanofluid using the artificial intelligence method and using design variables such as solid volume fraction and temperature. In this study, 6 optimization algorithms were used to predict and nu...

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Bibliographic Details
Main Authors: Mohammadreza Baghoolizadeh, Dheyaa J. Jasim, S. Mohammad Sajadi, Reza Rostamzadeh- Renani, Mohammad Rostamzadeh- Renani, Maboud Hekmatifar
Format: Article
Language:English
Published: Elsevier 2024-02-01
Series:Heliyon
Subjects:
Meta-heuristic
NSGA II
Correlation coefficient
Nanofluid
Pareto front
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844024023107

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http://www.sciencedirect.com/science/article/pii/S2405844024023107

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