@inproceedings{67c72738c1ee4c20a887b69863a17489,
title = "Coiling temperature optimal setting control model based on genetic algorithms and application in hot strip rolling mill",
abstract = "Coiling temperature is one of the most important targets of hot strip rolling. The coiling temperature can be controlled by laminar cooling system. A lot of measured data were got by many experiments in considering of the characteristics of hot strip rolling and the strip temperature change characteristics in laminar cooling area. To overcome the defects of traditional model, a new coiling temperature setting control model based on mended genetic algorithms neural network is set up. The new model has been used and results of industrial application show that the model has high precision. The temperature control error within ±20 °C(contract target) is 100\% while ± 10 °C is 93\%.",
keywords = "Coiling temperature, Genetic algorithms, Hot strip rolling, Neural networks, Optimal setting, Temperature control model",
author = "Zhang Dazhi and Ye Haili and Xiang Xiaofei",
year = "2010",
doi = "10.1109/iCECE.2010.151",
language = "英语",
isbn = "9780769540313",
series = "Proceedings - International Conference on Electrical and Control Engineering, ICECE 2010",
pages = "591--594",
booktitle = "Proceedings - International Conference on Electrical and Control Engineering, ICECE 2010",
note = "International Conference on Electrical and Control Engineering, ICECE 2010 ; Conference date: 26-06-2010 Through 28-06-2010",
}