Artificial Intelligence Modelling Approach for the Prediction of CO-Rich Hydrogen Production Rate from Methane Dry Reforming

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 H<sub>2</sub> production by methane dry re...

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Bibliographic Details
Main Authors: Bamidele Victor Ayodele, Siti Indati Mustapa, May Ali Alsaffar, Chin Kui Cheng
Format: Article
Language:English
Published: MDPI AG 2019-08-01
Series:Catalysts
Subjects:
artificial neural network
kinetic modeling
cobalt-praseodymium (III) oxide
CO-rich hydrogen
methane dry reforming
Online Access:https://www.mdpi.com/2073-4344/9/9/738

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