Artificial intelligence modelling approach for the prediction of CO-rich hydrogen production rate from methane dry reforming
This study investigates the applicability of the Leven–Marquardt algorithm, Bayesian regularization, and a scaled conjugate gradient algorithm as training algorithms for an artificial neural network (ANN) predictively modeling the rate of CO and H2 production by methane dry reforming over a Co/Pr2O3...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI
2019
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/26852/1/Artificial%20intelligence%20modelling%20approach%20for%20the%20prediction%20of%20CO.pdf http://umpir.ump.edu.my/id/eprint/26852/ https://doi.org/10.3390/catal9090738 https://doi.org/10.3390/catal9090738 |
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