On the basis of theoretic analysis and experiment, the new rolling force model has been developed.
通过理论推导和现场实验相结合，建立了新的轧制力模型。
Experiment results indicate that the designed rolling force model has better adaptive capability and high prediction accuracy.
试验研究证明，所设计模型具有良好的适应能力，提高了轧制力的预报精度。
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。
For improving the precision of prediction of rolling model, a new method using artificial neural networks of rolling force modeling is put forward.
为了提高轧制力模型预报值的精度，提出了一种基于人工神经网络的轧制力建模新方法。
The traditional rolling force model of 4-stand tandem cold strip mill at Anshan Iron and Steel Corporation was analyzed, and some defects were found out.
分析了鞍钢冷轧厂4机架冷连轧机轧制力模型，指出了其存在的主要缺陷，并提出了改进方案。
On the basis of analyzing factors to influence the rolling model of tandem cold strip mill and combining rolling theory with experiment, a new rolling force model was developed.
在分析冷连轧机轧制力模型各种影响因素的基础上，通过理论推导结合现场试验建立了新的轧制力模型。
Based on the rolling force model and field data of Baoshan steel plant, the rolling force during continuous hot strip rolling process is simulated by using the DEFORM-2D software.
应用DEFORM - 2d软件对带钢热连轧过程的轧制力进行了有限元模拟，并与宝钢轧制力模型进行了比较。
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。
Based on practical data trained by the neural network, the model enables to give better prediction result of rolling force.
网络在多次训练后对生产中的历史数据进行了轧制力预报，达到了较高的预报精度。
This paper presents an artificial neural network model to predict the rolling force to control hot-rolled strip strip thickness.
研究了热轧板带厚度控制中轧制力预报环节的局部逼近神经网络实现方法。
This model provides necessary theoretic basis for 304L stainless steel calculation of rolling force.
该模型可为计算304L不锈钢的轧制力提供理论依据。
The finite element model of HBeam rolling with and without deviation of vertical roller was established. The HBeam head displacement field and rolling force parameters were studied in detail.
利用有限元方法建立了立辊偏移前后H型钢轧制的有限元模型，研究了立辊轴线偏移时H型钢头部位移场和力能参数的变化规律。
The models can be used to predict strip surface roughness, arrange steel strip rolling order reasonably, decide the time of work roll off mill and modify the calculation model of rolling force.
这些模型可以用于生产中预测轧后带钢表面粗糙度、合理安排带钢轧制顺序、决定工作辊下机时间和修正轧制力计算模型。
Therefore, establishing the precise and practical rolling-force calculation model has become a research project with important applied worth in the continuous rolling-seamless steel pipe field.
因此，建立精确实用的轧制力计算模型，就成为连轧无缝钢管轧制领域内的一个具有重大应用价值的研究课题。
In order to improve the precision of the model, a new method using self adaption and artificial neural networks to predict rolling force was developed.
为了提高中厚板轧机轧制力的预报精度，采用轧制力模型自适应与人工神经元网络相结合的方法进行中厚板轧制力的在线预报。
Introduce the rolling force mathematic model used in pre-calculated rolling schedule and a new rolling force learning model based on feedback data from the instrument in rolling process.
介绍预计算轧制规程中所使用的轧制力模型，在此基础上根据轧制过程中的仪表反馈数据开发出一种新的轧制力自学习模型。
In order to control the rolling force, we must build the mathematic model of rolling force.
为了控制铸轧力，必须建立铸轧力控制数学模型。
The rolling force prediction models for the 1st & 2nd hot rolling mills in Bao Steel are analysed and compared with the general form of the force prediction model.
分析了宝钢一、二热轧精轧轧制力计算模型，并与轧制力计算模型的一般形式进行了比较。
This paper discusses using the neural network to predict the rolling force which is the key-point of the set-up model for the finisher of hot strip mill.
用神经元网络的方法代替传统轧制力模型的计算。解决与精轧机组设定模型有关的轧制力预报问题。
This paper discusses using the neural network to predict the rolling force which is the key-point of the set-up model for the finisher of hot strip mill.
用神经元网络的方法代替传统轧制力模型的计算。解决与精轧机组设定模型有关的轧制力预报问题。
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