A prediction model for the performance of solar photovoltaic-thermoelectric systems utilizing various semiconductors via optimal surrogate machine learning methods

A prediction model for the performance of solar photovoltaic-thermoelectric systems utilizing various semiconductors via optimal surrogate machine learning methods

This research focuses on finding the best surrogate performance prediction model for a solar photovoltaic-thermoelectric (PV-TE) module with different semiconductor materials. The need for a surrogate machine learning model arises due to the inefficiency of the current numerical simulations used to...

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Bibliographic Details
Main Authors: Hisham Alghamdi, Chika Maduabuchi, Abdullah Albaker, Ibrahim Alatawi, Theyab R. Alsenani, Ahmed S. Alsafran, Abdulaziz Almalaq, Mohammed AlAqil, Mostafa A.H. Abdelmohimen, Mohammad Alkhedher
Format: Article
Language:English
Published: Elsevier 2023-04-01
Series:Engineering Science and Technology, an International Journal
Subjects:
Artificial intelligence
Artificial neural networks
Photovoltaic-thermoelectric
Thermoelectric materials
Finite element method
Online Access:http://www.sciencedirect.com/science/article/pii/S221509862300040X

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http://www.sciencedirect.com/science/article/pii/S221509862300040X

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