Predict the Internal Corrosion Rate of Gas Pipeline with Artificial Neural Network

This paper adopts the artificial neural network to predict internal corrosive rate of gas pipeline. The predictable results show that the results obtained by the method is closed to the actual internal corrosion rate with a high accuracy. The writers consider that the artificial neural network is better than the stepwise regression analysis method, and suggest that this method can be used as a new method to predict internal corrosion rate of gas pipeline.