Application of Artificial Neural Networks for Estimation of the Reaction Rate in Methanol Dehydration

In this paper, the artificial neural network has been applied to estimate the reaction rate of methanol dehydration in dimethyl ether synthesis. The multilayer feed forward neural network with three inputs and one output has been trained with different algorithms and different numbers of neurons in the hidden layer. Two thirds of all training data are used for training of the network and the rest are used for testing of the generalization of the network. The accuracy of the proposed model was found to agree well with the experimental results over a wide range of experimental conditions. The results clearly depict that the neural network is a powerful tool to estimate the reaction rate and the designed neural network can be used instead of approximate and complex analytical equations.