Modeling the viscosity of nanofluids using artificial neural network and Bayesian support vector regression-Reference-Cited by-同舟云学术

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Modeling the viscosity of nanofluids using artificial neural network and Bayesian support vector regression

Published:2020-08-28 Issue:8 Volume:128 Page:085306
ISSN:0021-8979
Container-title:Journal of Applied Physics
language:en
Short-container-title:Journal of Applied Physics

Author:

Alade Ibrahim Olanrewaju¹,Rahman Mohd Amiruddin Abd¹,Hassan Amjed²,Saleh Tawfik A.³^ORCID

Affiliation:

1. Department of Physics, Faculty of Science, Universiti Putra Malaysia, 43400 UPM Serdang, Malaysia

2. Department of Petroleum, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran 31261, Saudi Arabia

3. Department of Chemistry, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran 31261, Saudi Arabia

Publisher

AIP Publishing

Subject

General Physics and Astronomy

Link

http://aip.scitation.org/doi/pdf/10.1063/5.0008977

Reference81 articles.

1. An experimental investigation into the thermal conductivity enhancement in oxide and metallic nanofluids

2. Recent advances in application of nanofluids in heat transfer devices: A critical review

3. A machine learning-based model to estimate the density of nanofluids of nitrides in ethylene glycol

4. Designing an artificial neural network to predict thermal conductivity and dynamic viscosity of ferromagnetic nanofluid

5. A reliable model to estimate the effective thermal conductivity of nanofluids

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