机构地区: 华南理工大学化学与化工学院传热强化与过程节能教育部重点实验室
出 处: 《化肥工业》 2000年第6期40-43,共4页
摘 要: 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。 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.
领 域: [化学工程]