Application of support vector regression and artificial neural network for prediction of specific heat capacity of aqueous nanofluids of copper oxide-Reference-Cited by-同舟云学术

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Application of support vector regression and artificial neural network for prediction of specific heat capacity of aqueous nanofluids of copper oxide

Published:2020-02 Issue: Volume:197 Page:485-490
ISSN:0038-092X
Container-title:Solar Energy
language:en
Short-container-title:Solar Energy

Author:

Alade Ibrahim Olanrewaju,Abd Rahman Mohd Amiruddin,Abbas Zulkifly,Yaakob Yazid,Saleh Tawfik A.

Publisher

Elsevier BV

Subject

General Materials Science,Renewable Energy, Sustainability and the Environment

Reference47 articles.

1. Investigation on the CPU nanofluid cooling;Al-Rashed;Microelectron. Reliab.,2016

2. Comparative study to use nano-(Al2O3, CuO, and SiC) with water to enhance photovoltaic thermal PV/T collectors;Al-Waeli;Energy Convers. Manag.,2017

3. Modeling and prediction of the specific heat capacity of Al2O3/water nanofluids using hybrid genetic algorithm/support vector regression model;Alade;Nano-Struct. Nano-Objects,2019

4. Predicting the specific heat capacity of alumina/ethylene glycol nanofluids using support vector regression model optimized with Bayesian algorithm;Alade;Sol. Energy,2019

5. Modeling thermal conductivity enhancement of metal and metallic oxide nanofluids using support vector regression;Alade;Adv. Powder Technol.,2017

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