|
|
Research on the Predictive Algorithm of Rolling Force Based on the Improved Fruit Flies Optimization Algorithm with LSSVM |
YANG Jing-ming1,2,GUO Qiu-chen1,SUN Hao1,MA Ming-ming1,CHE Hai-jun1,2,ZHAO Xin-qiu1,2 |
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 |
|
|
Abstract In the process of aluminum alloy plate finishing, rolling force is an important factor affecting the quality of plate. In order to meet the scene of the rolling forecast accuracy, improved fruit flies optimization algorithm (FOA) is combined with least square support vector machine (LSSVM) for rolling force prediction. The function of smell and the method of step length setting are improved. The grouping parallel search strategy is used. A new method based on the improved FOA-LSSVM is proposed for rolling force prediction. The method is used in simulation experiment of field data of aluminum strip, the results show that the prediction error data is in the range of ten percent, and eighty-four percent of these error data is in the range of five percent, the result shows that this method is better than the traditional model.
|
Received: 13 November 2014
Published: 29 July 2016
|
|
|
|
|
[1]Lee D,Lee Y. Application of neural-network for improving accuracy of roll-force model in hot-rolling mill[J]. Control Engineering Practice,2002,10(4): 473-478.
[2]赵志伟,杨景明,车海军,等.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.
[3]杨景明,马凤艳,车海军,等.基于最小二乘支持向量机的反向建模的铝合金变形抗力模型[J].计量学报,2013, 34(6): 532-536.
[4]赵新秋,刘正亮,杨景明,等.基于 ABC-LSSVM 的铝热连轧板凸度软测量建模[J].计量学报, 2014, 35(4): 323-326.
[5]程志强,马义中.基于鲁棒LS-SVM的控制图模式识别[J]. 计量学报, 2009,30 (6):580-582.
[6]陈治明,罗飞,黄晓红,等.基于混沌优化支持向量机的轧制力预测[J]. 控制与决策, 2009, 24(6): 808-811.
[7]Sims R B. The calculation of roll force and torque in hot rolling mills[J]. Proceedings of the Institution of Mechanical Engineers, 1954, 168(1): 191-200.
[8]Pan W T. A new fruit fly optimization algorithm: taking the financial distress model as an example[J]. Knowledge-Based Systems, 2012, 26: 69-74. |
|
|
|