Viscosity Prediction of Different Ethylene Glycol/Water Based Nanofluids Using a RBF Neural Network
In this study, a radial basis function (RBF) neural network with three-layer feed forward architecture was developed to effectively predict the viscosity ratio of different ethylene glycol/water based nanofluids. A total of 216 experimental data involving CuO, TiO2, SiO2, and SiC nanoparticles were...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2017-04-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2076-3417/7/4/409 |