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将人工神经网络应用于木材干燥控制研究中,建立可用于木材含水率预测的时延神经网络基准模型,并给出其网络辨识结构。通过3个树种的实际干燥数据对所建立的网络模型进行训练和验证,仿真结果表明预测模型是可行而有效的,具有较好的动态跟踪能力和预报特性,实现了木材干燥基准的数学模型化,对进一步优化木材干燥基准实施与控制具有重要的指导意义和应用价值。
The artificial neural network is applied in the research of wood drying control, and a time delay neural network reference model that can be used to predict the wood moisture content is established. The network identification structure is also given. The established network model is trained and validated by the actual drying data of the three species. The simulation results show that the prediction model is feasible and effective, has good dynamic tracking ability and forecasting characteristics, and realizes mathematical modeling of the wood drying benchmark , Which has important guiding significance and application value to further optimize the implementation and control of wood drying standards.