Research on self-learning of parameter control model for heavy rail straightening

Parameter control model for heavy rail straightening gives a rolling reduction by calculation, and when the rolling reduction can not meet the technical requirements, it need to establish a self-learning model to redistribute of rolling reduction.The trained ANN (Artificial Neural Network) in self-learning model can be used to predict the next distribution coefficient of the calculation model, and get a better input values of rolling reduction, it uses RBFNN algorithm to study the correlation between the parameters from the historical data stored in the database intelligently, and then give a optimal adjusted value.