Artificial Neural Network Modeling of Hydrogen-rich Syngas Production from Methane Dry Reforming over Novel Ni/CaFe2O4 Catalysts
In this study, the application of artificial neural networks (ANN) for the modeling of hydrogen-rich syngas produced from methane dry reforming over Ni/CaFe2O4 catalysts was investigated. Multi-layer perceptron (MLP) and radial basis function (RBF) neural network architectures were employed for the...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier Ltd
2016
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/13179/ http://umpir.ump.edu.my/id/eprint/13179/ http://umpir.ump.edu.my/id/eprint/13179/ http://umpir.ump.edu.my/id/eprint/13179/1/Artificial%20Neural%20Network%20Modeling%20Of%20Hydrogen-Rich%20Syngas%20Production%20From%20Methane%20Dry%20Reforming%20Over%20Novel%20Ni-CaFe2O4catalysts.pdf |