By comparison with actual measurement parameters, this conesquence is confirmed to be more accurate in the prediction of the rolling force.
通过与现场实测数据的比较，证明了本解法能更准确的预报冷轧薄板的轧制力。
The result of on-line application indicated that rolling force model has good precision of prediction with an error less than 5%.
现场在线应用结果表明：给出的轧制力模型具有良好的预测精度，预测误差可以控制在5%以内。
To improve the precision and efficiency of rolling force prediction on tandem cold rolling mill, a neural network model combined with ant colony algorithm is presented.
为提高冷连轧机轧制力的预报精度和预报速度，用蚁群算法和神经网络相结合的方法进行轧制力预报模型设计。
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