Prediction of the thermal behavior of multi-walled carbon nanotubes-CuO-CeO2 (20-40-40)/water hybrid nanofluid using different types of regressors and evolutionary algorithms for designing the best artificial neural network modeling

Prediction of the thermal behavior of multi-walled carbon nanotubes-CuO-CeO2 (20-40-40)/water hybrid nanofluid using different types of regressors and evolutionary algorithms for designing the best artificial neural network modeling

For conducting an analysis of the experimental data, it is imperative to establish a mathematical correlation between the input and output variables. This entails executing a curve fitting or regression procedure on the data, for which numerous methodologies exist. Within the scope of present invest...

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Xehetasun bibliografikoak
Egile Nagusiak: Reza Rostamzadeh-Renani, Mohammadreza Baghoolizadeh, S. Mohammad Sajadi, Mostafa Pirmoradian, Mohammad Rostamzadeh-Renani, Sh. Baghaei, Soheil Salahshour
Formatua: Artikulua
Hizkuntza:English
Argitaratua: Elsevier 2023-12-01
Saila:Alexandria Engineering Journal
Gaiak:
Thermal behavior
Hybrid nanofluid
Regressors
Evolutionary algorithms
Artificial neural network modeling
Sarrera elektronikoa:http://www.sciencedirect.com/science/article/pii/S1110016823009705

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http://www.sciencedirect.com/science/article/pii/S1110016823009705

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