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.
杨景明,郭秋辰,孙浩,马明明,车海军,赵新秋. 基于改进果蝇算法与最小二乘支持向量机的轧制力预测算法研究[J]. 计量学报, 2016, 37(5): 505-508.
YANG Jing-ming,GUO Qiu-chen,SUN Hao,MA Ming-ming,CHE Hai-jun,ZHAO Xin-qiu. Research on the Predictive Algorithm of Rolling Force Based on the Improved Fruit Flies Optimization Algorithm with LSSVM. Acta Metrologica Sinica, 2016, 37(5): 505-508.
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2016, Vol. 37 
