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修正遗传神经网络预测中厚板轧机轧制力
Application of Modified GA-ANN Network to Rolling Force Prediction
【摘要】 在实际生产过程中,传统轧制力数学模型存在较大误差,影响计算精度.提出将BP网络与修正遗传算法相结合,利用BP网络的指导性搜索思想和遗传算法的全局搜索能力预测中厚板轧机轧制力,并建立预测模型.同时,根据模型编制相应的程序及界面.以邯钢中板厂、普阳中板厂现场数据为基础,通过数据优选,选择较优数据进行离线轧制力预测,预测精度优于传统的数学模型,预报精度的相对误差可以控制在4%以内,能够满足生产需要.
【Abstract】 In the process of real production,the calculation results by conventional models have relatively big errors in the prediction of rolling force.It is therefore suggested to combine the BP network with modified GA algorithm to develop a prediction model,i.e.,predicting the rolling force to be applied to medium thick plates by means of the guidable idea about search from BP network and the capability of global search from genetic algorithm.Moreover,the corresponding program and interface were given according to the prediction model.Based on the in-situ data taken from Handan and Puyang plate rolling mills,some optimal data was selected to predict the off-line rolling force.The results showed that the predicted accuracy resulting from the model developed is higher than that from conventional models,i.e.,the relative error is within 4%,thus meeting the actual requirement for plate rolling.
【Key words】 ANN(artificial neural network); BP algorithm; GA(genetic algorithm); rolling force prediction; mathematic model;
- 【文献出处】 东北大学学报(自然科学版) ,Journal of Northeastern University(Natural Science) , 编辑部邮箱 ,2008年10期
- 【分类号】TG335.5
- 【被引频次】14
- 【下载频次】286