A forecast model based on the BP neural network used in refinery´s steel equipment´s corrosion

The forecasting of the corrosion of refinery´s steel equipments shows great importance in preventing the accident. Considering the numerous factors affecting the corroding of refinery´s steel equipments, which are uneasily predictable and with complex relationships, this paper proposed a new technology based on the BP neural network technology used in forecasting of the corrosion of refinery´s steel equipments. A new model is also built and implemented in this paper. Finally, the experimental results prove the feasibility of the new model and the forecasted results by this new model fixes well with the sample data set.