The application of data mining (DM) on hot strip rolling was introduced to improve the prediction accuracy of a model for estimating coiling temperature on a run-out table. Due to nonlinear and time-variation characteristics of coiling temperature control, conventional methods with simple mathematical models and a coarse adaptation scheme are not sufficient to obtain a good prediction of coiling temperature. A new method establishing a control model of coiling temperature is proposed based on the on-line information processing technology, which adopts DM to mine the database of laminar cooling...