Artificial Neural Network Based Model for Calculating the Flow Composition Influence of Solid Oxide Fuel Cell

Abstract

The paper presents use of an artificial neural network (ANN) for predicting the thermalflow behavior of a solid oxide fuel cell with no algorithmic solution merely by utilizing available experimental data. The error backpropagation algorithm was used for an ANN training procedure.