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Prediction of coiling temperature on run-out table of hot strip mill using data mining

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成果类型:
期刊论文、会议论文
作者:
Xie, H. B.*;Jiang, Z. Y.;Liu, X. H.;Wang, G. D.;Tieu, A. K.
通讯作者:
Xie, H. B.
作者机构:
[Xie, H. B.] Univ Wollongong, Sch Mech Mat & Methatron Engn, Wollongong, NSW 2522, Australia.
Northeastern Univ, State Key Lab Rolling & Automat, Shenyang 110004, Liaoning, Peoples R China.
Nanhua Univ, Sch Mech Engn, Hunan 421001, Peoples R China.
通讯机构:
[Xie, H. B.] U
Univ Wollongong, Sch Mech Mat & Methatron Engn, Wollongong, NSW 2522, Australia.
语种:
英文
关键词:
data mining;regression;neural network;hot strip mill;coiling temperature;prediction
期刊:
Journal of Materials Processing Technology
ISSN:
0924-0136
年:
2006
卷:
177
期:
1-3
页码:
121-125
会议名称:
11th International Conference on Metal Forming 2006
会议时间:
SEP 11-13, 2006
会议地点:
Univ Birmingham, Birmingham, ENGLAND
会议主办单位:
Univ Wollongong, Sch Mech Mat & Methatron Engn, Wollongong, NSW 2522, Australia.^Northeastern Univ, State Key Lab Rolling & Automat, Shenyang 110004, Liaoning, Peoples R China.^Nanhua Univ, Sch Mech Engn, Hunan 421001, Peoples R China.
出版地:
PO BOX 564, 1001 LAUSANNE, SWITZERLAND
出版者:
ELSEVIER SCIENCE SA
机构署名:
本校为其他机构
院系归属:
机械工程学院
摘要:
The application of data mining (DM) on hot strip rolling was introduced to improve the prediction accuracy of a model for estimating coiling temperature on a run-out table. Due to nonlinear and time-variation characteristics of coiling temperature control, conventional methods with simple mathematical models and a coarse adaptation scheme are not sufficient to obtain a good prediction of coiling temperature. A new method establishing a control model of coiling temperature is proposed based on the on-line information processing technology, which adopts DM to mine the database of laminar cooling...

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