Northeastern University

Lin Wang

Dianhua Zhang

Yuejiao Han

Xu Li

Feng Luan

Yan Wu

Provided is an LSTM-based hot-rolling roll-bending force predicting method including the steps of acquiring final rolling data of a stand of a stainless steel rolling mill when performing a hot rolling process, and dividing the data into a training set traindata and a test set testdata; normalizing the traindata; building a matrix P; using a last row of the matrix P as a label of the training set, namely a true value; calculating and updating an output value and the true value of a network; after network training is completed, taking the last m output data of the LSTM network as an input at a next moment, and then obtaining an output of the network at the next moment, wherein the output is a predicted value of the roll-bending force at the next moment; repeating the steps until a sufficient number of prediction data is obtained; and comparing the processed data with the true value in the testdata to check the validity of the network.

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Shenyang, China

Lin Wang