Diagonal Recurrent Neural Network and Its Application in Mechanical Property Prediction of 82B Steel

Two key problems of modeling nonlinear system using neural network are discussed.One is the type of neural network,the other is to get the input of network when the type of network is defined.Because the BP network can′t update in time and has slow rate of convergence,DRNN network can realize the nonlinear map dynamically,and can trace the change of the model,so it has better predicting result.It first excavated some technological conditions related to the quality index by association rule,then the appropriate input and output of the model could be found by combining the worker′s experience,finally the 82B steel was optimized using DRNN(Diagonal Recurrent Neural Network) network,and a better result was obtained.