Research of Elman Neural Networks Model for Wood Drying Process
Jiang Bi · Anhui nongye kexue · 2014
[Objective]The aim was to study Elman neural networks model in wood drying process. [Method] Based on artificial neural network theory,the Elman neural network was used to build wood drying process model. Aiming at the characters of wood drying process,it has been built the wood moisture content model by Elman neural networks algorithm,which is using the data of temperature and humidity of the wood. [Result]By using the actual drying process data to verify the accuracy of the model,the result shows that it can build the model,which could maintain higher prediction accuracy,stronger associative memory ability and optimization capabilities for data,by a small amount of data. [Conclusion]The wood drying process model built by Elman neural network is precision,and this model could have significant meaning for improving the control level of wood drying process.