Comparison of prediction methods of PV/T nanofluid and nano-PCM system using a measured dataset and artificial neural network-Reference-Cited by-同舟云学术

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Comparison of prediction methods of PV/T nanofluid and nano-PCM system using a measured dataset and artificial neural network

Published:2018-03 Issue: Volume:162 Page:378-396
ISSN:0038-092X
Container-title:Solar Energy
language:en
Short-container-title:Solar Energy

Author:

Al-Waeli Ali H.A.,Sopian K.,Kazem Hussein A.,Yousif Jabar H.,Chaichan Miqdam T.,Ibrahim Adnan,Mat Sohif,Ruslan Mohd Hafidz

Funder

National University of Malaysia

Solar Energy Research Institute

Makmal Morfologi CRIM

Makmal Pencirian Fizikal

Publisher

Elsevier BV

Subject

General Materials Science,Renewable Energy, Sustainability and the Environment

Reference88 articles.

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2. Hybrid nanofluids based on Al2O3, TiO2 and SiO2: numerical evaluation of different approaches;Adriana;Int. J. Heat Mass Transf.,2017

3. Predictive control of an integrated PV-diesel water and power supply system using an artificial neural network;Al-Alawi;Renew. Energy,2007

4. Performance of PVT solar collector with compound parabolic concentrator and phase change materials;Al-Imam;Energy Build.,2016

5. Characterisation of Si-crystalline PV modules by artificial neural networks;Almonacid;Renew. Energy,2009

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