Enhancing solar energy conversion efficiency: Thermophysical property predicting of MXene/Graphene hybrid nanofluids via bayesian-optimized artificial neural networks

Enhancing solar energy conversion efficiency: Thermophysical property predicting of MXene/Graphene hybrid nanofluids via bayesian-optimized artificial neural networks

Accurately predicting thermo-physical properties (TPPs) of MXene/graphene-based nanofluids is crucial for photovoltaic/thermal solar systems, driving focused research on developing precise TPP predictive models. This study presents optimized multi-layer perceptron neural network (MLPNN) models, leve...

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Bibliographic Details
Main Authors: Dheyaa J. jasim, Husam Rajab, As'ad Alizadeh, Kamal Sharma, Mohsen Ahmed, Murizah Kassim, S. AbdulAmeer, Adil A. Alwan, Soheil Salahshour, Hamid Maleki
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Results in Engineering
Subjects:
Solar energy conversion
PVT solar panels
Artificial neural network
Machine learning
MXene
Graphene
Online Access:http://www.sciencedirect.com/science/article/pii/S2590123024011137
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