Experimental study for developing an accurate model to predict viscosity of CuO–ethylene glycol nanofluid using genetic algorithm based neural network-Reference-Cited by-同舟云学术

Experimental study for developing an accurate model to predict viscosity of CuO–ethylene glycol nanofluid using genetic algorithm based neural network

Published:2018-10 Issue: Volume:338 Page:383-390
ISSN:0032-5910
Container-title:Powder Technology
language:en
Short-container-title:Powder Technology

Author:

Hemmat Esfe Mohammad,Bahiraei Mehdi^ORCID,Mahian Omid

Publisher

Elsevier BV

Subject

General Chemical Engineering

Reference43 articles.

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2. Experimental evaluation, sensitivity analyzation and ANN modeling of thermal conductivity of ZnO-MWCNT/EG-water hybrid nanofluid for engineering applications;Esfe;Appl. Therm. Eng.,2017

3. Comparison of experimental data, modelling and non-linear regression on transport properties of mineral oil based nanofluids;Esfahani;Powder Technol.,2017

4. Thermal conductivity enhancement of SiO2–MWCNT (85: 15%)–EG hybrid nanofluids;Esfe;J. Therm. Anal. Calorim.,2017

5. Convective flow of ferrofluid due to a curved stretching surface with homogeneous-heterogeneous reactions;Imtiaz;Powder Technol.,2017

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