New Training Algorithm for the Process Neural Network and Its Application

A new training algorithm for the process neural network is presented when it is used to model an industrial process.Considering the process variables data with the prosperities of being discrete and including some pseudo ones,the data pretreatment has to be required,and then a new algorithm based on discrete Walsh conversion was used to convert the sampled data to be the direct inputs,then it can shorten the network training time and improve the network mapping precision.The model of the process neural network with the new training algorithm and two hidden-layers structure was applied to forecast the mycelium density of the glutamate fermentation process,and the simulation results were excellent.