Abstract:Against the general drying process analysis method, the drying process to take orthogonal test results of the neural network modeling, and to conduct a detailed study, The BP neural networks is of practical significance to the drying process control mathematical model, the results are analyzed, thus achieving optimal results of the pilot control. This article gives the flash drying brewer's grain test data collection of neural network methods, orthogonal experiment conducted experiments on different operating conditions of brewer's grain moisture content for the test, as well as visual analysis, variance analysis and neural network analysis of the differences and outlined the reasons. In addition, the drying of materials basic unit operation for a detailed explanation.
The main contents of thesis has:（1）which describes the advantages of orthogonal test, test orthogonal arrangement principles and methods of presentation and realized;（2）The neural network modeling method and the principle of achieving modeling;（3）to carry out a pilot data collection of neural network methods, statistical regression modeling, and using the model trend analysis;（4）Apply the result analysis, comparison and eva luation physically.
Moreover,this thesis makes use of artificial neural network modelling to possess singly not line to reflect the mathematics model of the ability of shooting establishment dry process,and guide production in order to according to this model.
Keywords: Neural network modeling; Drying process; Orthogonal test; Visual analysis; Analysis of variance
