Artificial Neural Network for Combined Steam-Carbon Dioxide Reforming of Methane

The CH₄ conversion, CO₂ conversion, and H₂/CO ratio were set as dependent variables, as the feed rate, flow rate and reaction temperature as independent variables in the complex reaction of methane. We used the Artificial Neural Network (ANN) technique to build a model of the process. The ANN technique was able to predict the reforming process with higher accuracy due to the training capability. The reaction temperature has the greatest effect on the CO₂-CH₄ reforming reaction. This is because the catalytic reaction temperature has a direct influence on the thermodynamic value and the reaction rate and the equilibrium state.