人工神经网络在甲烷转化操作预报中的应用研究

利用人工神经网络中较经典的BP网络模型的网络结构和学习原理，对合成氨车间转化工段的数据利用神经网络模型进行指导操作调优。结果表明，该方法预报的结果与实际生产数据误差在合理范围之内，可作为甲烷转化工段生产控制、操作调优的辅助分析手段。

Study of Use of Artificial Neuron Networkin Prediction of Methane Reforming Operation

By making use of the network structure of the classical BP network model in the artifical neuron network and the principle of learning, the data from the reforming section of the ammonia plant are instructed for operation optimization with the neuron network model. The results show that the predicted results of the method and the actual production data have an error within the rational range, so the method can be regarded as an auxiliary analytical means for production control and operation optimization in the methane reforming section.