Abstract：The neural network (NN) models can be used to enhance the prediction of rolling parameters instead of traditional mathematical models.A NN model for tandem cold rolling parameter prediction was designed on the base of rolling theories. Aiming to avoid the disadvantages of the BackPropagation(BP) Algorithm, of which the speed of constringency is lower and the local minimum is easy to be got, a global optimization algorithm called Simulated Annealing Algorithm is used to help the neural network to possess at high speed and precisely.The high speed of constringency, stability and reliability of the method was confirmed by rolling force prediction.
杨景明;刘舒慧;车海军;孙晓娜. 一种结合模拟退火算法的BP网络冷连轧参数预报模型[J]. 钢铁, 2008, 43(7): 55-0.
YANG Jingming;LIU Shuhui;CHE Haijun;SUN Xiaona. A Simulated Annealing AlgorithmBP Network Model for Tandem Cold Rolling Parameter Prediction. Iron and Steel, 2008, 43(7): 55-0.
2008, Vol. 43 
