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利用人工神经网络技术,建立了BP网络模型,通过网络的学习训练,比较准确地预测了粉体密相气力输送过程中的管道压降,预测准确率在93.3％以上,表明该方法可以作为密相气力输送研究中的一种有效的辅助手段。
The artificial neural network technology is used to establish the BP network model. Through the network learning and training, the pipeline pressure drop in the dense phase pneumatic conveying process is predicted more accurately, and the prediction accuracy is above 93.3%, which shows that the method can be used as a close An Effective Auxiliary Means in the Study of Phase Pneumatic Conveying.