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利用神经网络建立了木材干燥的温湿度模型,给出了其时延神经网络辨识结构。分别提出温、湿度控制模型(控制信号与温、湿度之间的关系模型)和木材干燥基准模型(温、湿度与木材含水率之间的关系模型),并利用实验干燥窑得到的实际数据进行了仿真研究。仿真结果表明,利用此方法建模是可行的,所建模型是有效的。图10参16。
The temperature and humidity model of wood drying was established by using neural network, and the identification structure of time-delay neural network was given. The temperature and humidity control models (the relationship between control signals and temperature and humidity) and the wood drying reference model (the model of the relationship between temperature, humidity and wood moisture content) are proposed respectively. The actual data obtained from the experimental kilns Simulation research. The simulation results show that it is feasible to use this method to model the model and the model is effective. Figure 10 Reference 16.