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In order to improve the control precision of strip coiling temperature for hot strip mill, the BP neural network was combined with mathematical model to calculate convective heat-transfer coefficient of laminar flow cooling. The off-line calculated results indicate that the standard deviation of coiling temperature prediction is reduced by 22.84 % with the convective heat-transfer coefficient calculated by BP neural network. The prospects of this method for on-line application are bright. This method is more helpful to increasing the control precision of coiling temperature for hot strip steel.