Evaluation of electrical efficiency of photovoltaic thermal solar collector

Evaluation of electrical efficiency of photovoltaic thermal solar collector

In this study, machine learning methods of artificial neural networks (ANNs), least squares support vector machines (LSSVM), and neuro-fuzzy are used for advancing prediction models for thermal performance of a photovoltaic-thermal solar collector (PV/T). In the proposed models, the inlet temperatur...

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Bibliographic Details
Main Authors: Mohammad Hossein Ahmadi, Alireza Baghban, Milad Sadeghzadeh, Mohammad Zamen, Amir Mosavi, Shahaboddin Shamshirband, Ravinder Kumar, Mohammad Mohammadi-Khanaposhtani
Format: Article
Language:English
Published: Taylor & Francis Group 2020-01-01
Series:Engineering Applications of Computational Fluid Mechanics
Subjects:
renewable energy
neural networks (nns)
adaptive neuro-fuzzy inference system (anfis)
least square support vector machine (lssvm)
photovoltaic-thermal (pv/t)
hybrid machine learning model
Online Access:http://dx.doi.org/10.1080/19942060.2020.1734094

Internet

http://dx.doi.org/10.1080/19942060.2020.1734094

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