Synergizing neural networks with multi-objective thermal exchange optimization and PROMETHEE decision-making to improve PCM-based photovoltaic thermal systems

Synergizing neural networks with multi-objective thermal exchange optimization and PROMETHEE decision-making to improve PCM-based photovoltaic thermal systems

This study addresses the integration of machine learning (ML) and artificial intelligence (AI) for optimizing photovoltaic-thermal (PVT) systems. While ML modeling has become prevalent in this field, a significant gap remains in combining ML with AI-based optimization and decision-making methods to...

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Bibliographic Details
Main Authors: Yongxin Li, Ali Basem, As'ad Alizadeh, Pradeep Kumar Singh, Saurav Dixit, Hanaa Kadhim Abdulaali, Rifaqat Ali, Pancham Cajla, Husam Rajab, Kaouther Ghachem
Format: Article
Language:English
Published: Elsevier 2025-04-01
Series:Case Studies in Thermal Engineering
Subjects:
Photovoltaic thermal system
Machine learning
Multi-objective thermal exchange optimization
Multi-criteria decision-making
Mathematical modeling
Renewable energy optimization
Online Access:http://www.sciencedirect.com/science/article/pii/S2214157X2500111X
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