The application of the Synchronous improved grey-neural network model in predicting of oil-gas pipeline corrosion rate

With much affect factors, the corrosion of pipeline under the complicated surroundings is not avoided. Leakage of gas will affect the running of transportation system, and lead to the happening of accidents, the damage on the personnel and property, as well as the pollution of environmental and waste of energy sources. So, the prediction of the corrosion rate and its´ law have important interest for controlling and reducing incidents of gas. The Synchronous improved grey-neural network Model has been established based on the improved grey model and the improved neural network model. This new model was used to predict the tendency of corrosion rate based on actual data. The maximal error and the average error is 1.24% and 0.48%, respectively. Compared with the models of the relative references, it shows this new model can get the best predicting result. It shows this new model is dependable and rational, and has great application value.