Prediction of Rolling Force Based on Artificial Bee Colony Algorithm and Back Propagation Neural Network in Aluminum Hot Tandem Rolling
ZHAO Zhi-wei1,2,3, YANG Jing-ming1,2, CHE Hai-jun1,2, HU Zi-yu1, WANG Xi1
1.Key Lab of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao, Hebei 066004,China;
2.National Engineering Research Center for Equipment and Technology of Cold Strip Rolling, Qinhuangdao, Hebei 066004, China;
3.Department of Computer Science and Technology, Tangshan College, Tangshan, Hebei 063000, China
Abstract：After analysing the traditional mathematic model of rolling force, a prediction method of rolling force based on the artificial bee colony Algorithm and back propagation neural network is presented, which is used in aluminum hot tandem rolling. The initial weights and threshold values of back propagation neural network are optimized by artificial bee colony algorithm. The training and testing samples are collected from the finishing mills. Comparing with the Sims mathematical model and back propagation neural network, the experimental results show that the prediction accuracy and error of rolling force is superior to that of the traditional methods.
赵志伟, 杨景明, 车海军, 呼子宇, 王茜. 基于人工蜂群算法与反向传播神经网络的铝热连轧轧制力预测[J]. 计量学报, 2014, 35(2): 157-160.
ZHAO Zhi-wei, YANG Jing-ming, CHE Hai-jun, HU Zi-yu, WANG Xi. Prediction of Rolling Force Based on Artificial Bee Colony Algorithm and Back Propagation Neural Network in Aluminum Hot Tandem Rolling. Acta Metrologica Sinica, 2014, 35(2): 157-160.
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