Applications of intelligent methods in solar heaters: an updated review

Heating and thermal comfort have remarkable share of final energy consumption. Until now, most of the demand for heating applications in buildings is supplied by fossil fuels and electrical technologies. Concerning the exhaustion of fossil fuels in the future and the environmental problems related t...

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Main Authors: Alhuyi Nazari M., Mukhtar A., Yasir A.S.H.M., Rashidi M.M., Ahmadi M.H., Blazek V., Prokop L., Misak S.
Other Authors: 57197717697
Format: Review
Published: Taylor and Francis Ltd. 2024
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spelling my.uniten.dspace-345802024-10-14T11:20:49Z Applications of intelligent methods in solar heaters: an updated review Alhuyi Nazari M. Mukhtar A. Yasir A.S.H.M. Rashidi M.M. Ahmadi M.H. Blazek V. Prokop L. Misak S. 57197717697 57195426549 58518504200 57189276752 55016898100 57195261596 23393638900 34977261800 artificial neural network intelligent methods renewable energy Solar heaters Heating and thermal comfort have remarkable share of final energy consumption. Until now, most of the demand for heating applications in buildings is supplied by fossil fuels and electrical technologies. Concerning the exhaustion of fossil fuels in the future and the environmental problems related to their consumption, making use of renewable energy sources can be a practical alternative. On this point, solar energy is an appropriate source to be applied for heating by utilizing different technologies. The function and output of solar heaters depends on numerous factors, and this causes difficulties in the prediction of their performance and modelling. In this scenario, intelligent techniques are helpful and have been used by several scholars in recent years. This paper reviews proposed models for the prediction of the performance of different solar heaters. The literature review reveals that artificial neural Networks represent one of the most used approaches for the performance prediction of solar heaters however, other intelligent techniques, namely support vector machines, have been used for this purpose too. Moreover, it is found that these methods have the ability to predict with great precision by applying the appropriate approach and architecture. In addition, it can be noted that the function of the models generated based on intelligent techniques are associated with some elements such as the employed function and architecture of the model. � 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. Final 2024-10-14T03:20:49Z 2024-10-14T03:20:49Z 2023 Review 10.1080/19942060.2023.2229882 2-s2.0-85166181340 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166181340&doi=10.1080%2f19942060.2023.2229882&partnerID=40&md5=31fd80f63b3d6e33a1136d44951c6741 https://irepository.uniten.edu.my/handle/123456789/34580 17 1 2229882 All Open Access Gold Open Access Taylor and Francis Ltd. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic artificial neural network
intelligent methods
renewable energy
Solar heaters
spellingShingle artificial neural network
intelligent methods
renewable energy
Solar heaters
Alhuyi Nazari M.
Mukhtar A.
Yasir A.S.H.M.
Rashidi M.M.
Ahmadi M.H.
Blazek V.
Prokop L.
Misak S.
Applications of intelligent methods in solar heaters: an updated review
description Heating and thermal comfort have remarkable share of final energy consumption. Until now, most of the demand for heating applications in buildings is supplied by fossil fuels and electrical technologies. Concerning the exhaustion of fossil fuels in the future and the environmental problems related to their consumption, making use of renewable energy sources can be a practical alternative. On this point, solar energy is an appropriate source to be applied for heating by utilizing different technologies. The function and output of solar heaters depends on numerous factors, and this causes difficulties in the prediction of their performance and modelling. In this scenario, intelligent techniques are helpful and have been used by several scholars in recent years. This paper reviews proposed models for the prediction of the performance of different solar heaters. The literature review reveals that artificial neural Networks represent one of the most used approaches for the performance prediction of solar heaters
author2 57197717697
author_facet 57197717697
Alhuyi Nazari M.
Mukhtar A.
Yasir A.S.H.M.
Rashidi M.M.
Ahmadi M.H.
Blazek V.
Prokop L.
Misak S.
format Review
author Alhuyi Nazari M.
Mukhtar A.
Yasir A.S.H.M.
Rashidi M.M.
Ahmadi M.H.
Blazek V.
Prokop L.
Misak S.
author_sort Alhuyi Nazari M.
title Applications of intelligent methods in solar heaters: an updated review
title_short Applications of intelligent methods in solar heaters: an updated review
title_full Applications of intelligent methods in solar heaters: an updated review
title_fullStr Applications of intelligent methods in solar heaters: an updated review
title_full_unstemmed Applications of intelligent methods in solar heaters: an updated review
title_sort applications of intelligent methods in solar heaters: an updated review
publisher Taylor and Francis Ltd.
publishDate 2024
_version_ 1814061062311378944
score 13.214268