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- W2368285413 abstract "In view of the complexity of laminar cooling process of hot-rolled strip, the configuration and mathematical model of air and water cooling of the laminar cooling system in a domestic hot rolling mill were discussed. The model is combined with BP neural network to predict how much the measured value of strip's coiling temperature deviates from its target value. The predicted results prove that combining BP neural network with the model is beneficial to the deviation prediction and, further, to the readjustment of the relevant parameters in the model. Then it is available to control the coiling temperature with high accuracy. Compared with the standard deviation as controlled conventionally by a mathematical model only, the new approach shows that the deviation is decreased by 21.94%." @default.
- W2368285413 created "2016-06-24" @default.
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- W2368285413 date "2005-01-01" @default.
- W2368285413 modified "2023-09-25" @default.
- W2368285413 title "Improving Control Accuracy of Coiling Temperature on Hot Strip Mill by Artificial Neural Network" @default.
- W2368285413 hasPublicationYear "2005" @default.
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