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Optimization Design of Rolling Schedules with Rolling Force Self-learning

机译:具有轧制力自学习的轧制进度计划的优化设计

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摘要

Single and multi-object optimization planning are presented for 1370mm tandem cold rolling schedules separately, in which, BP neural network with self-learning function is adopted to predict the rolling force instead of traditional models. Analysis and comparison with existing schedules are offered, and the performance of the optimal rolling schedules is satisfying.
机译:分别针对1370mm冷连轧方案制定了单目标和多目标优化计划,其中采用具有自学习功能的BP神经网络代替传统模型来预测轧制力。提供了与现有计划的分析和比较,并且最佳轧制计划的性能令人满意。

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