【摘要】 木材干燥是一个复杂的非线性系统 ,由于木材结构复杂且具有多样性和变异性 ,因此要建立一个理想的符合木材干燥过程的模型是很困难。本文利用动态递归神经网络的特点 ,提出了基于动态递归神经网络的木材干燥模型辨识方法 ,给出了动态递归状态 -输出神经网络的结构和学习算法。并通过对辨识得到的模型的仿真结果 ,表明了本文所建立的模型是有效的更多还原

【Abstract】 For wood having variety, complexity and variability, wood drying process is a complicated nonlinear system. So it is difficult to get an ideal model for wood drying. Utilizing the properties of dynamical recurrent neural networks, an identification approach based on it for the model of wood drying was presented in this paper. And the structure of the dynamical recurrent state_output neural networks and the learning algorithms were given. The simulation results showed that the model is effective.更多还原