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冷连轧机出口厚度人工神经网络快速预报
Prediction on Exit Thickness of Cold Continuous Rolling Mill Using Neural Network
【摘要】 采用改进的BP网络Levenberg-Marquardt优化算法对冷连轧机出口厚度进行快速预报,此网络μ参量可自适应调整,收敛速度快。冷连轧生产出口厚度预报精度大为提高,为冷连轧出口厚度预报提供了一条准确高效的新途径。
【Abstract】 Improved BP neural network which adopted Lev-enberg-Marquardt optimized algorithm has been used to predict thickness. In this algorithm, the parameter μ can be adaptive adjusted, and network convergence speed is higher than before. Thickness predicting precision was improved. A new precise and high efficiency way for cold continuous rolling exit thickness prediction have been provided.
【关键词】 冷连轧;
出口厚度;
神经网络;
预报;
【Key words】 cold continuous rolling process; exit thickness; neural network; predict.;
【Key words】 cold continuous rolling process; exit thickness; neural network; predict.;
【基金】 国家自然基金资助重点项目(项目编号:50035010);教育部科技重点资助项目(项目编号:00144)。
- 【文献出处】 燕山大学学报 ,Journal of Yanshan University , 编辑部邮箱 ,2003年01期
- 【分类号】TG334.9
- 【被引频次】12
- 【下载频次】96