Prediction of bending force in the hot strip rolling process using artificial neural network and genetic algorithm (ANN-GA)

An artificial neural network (ANN) optimized by genetic algorithm (GA) is an established prediction model of bending force in hot strip rolling. The data are collected from factory of steel manufacture. Entrance temperature and thickness, exit thickness, strip width, rolling force, rolling speed, ro...

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Veröffentlicht in:	International journal of advanced manufacturing technology Jg. 93; H. 9-12; S. 3325 - 3338
Hauptverfasser:	Wang, Zhen-Hua, Gong, Dian-Yao, Li, Xu, Li, Guang-Tao, Zhang, Dian-Hua
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer London 01.12.2017 Springer Nature B.V
Schlagworte:	Artificial neural networks Back propagation Back propagation networks Bayesian analysis Bending CAE) and Design Computer-Aided Engineering (CAD Correlation coefficients Crossovers Engineering Entrances Errors Fitness Genetic algorithms Independent variables Industrial and Production Engineering Mathematical models Mechanical Engineering Media Management Model accuracy Neural networks Optimization Original Article Performance evaluation Prediction models Rolling speed Root-mean-square errors Schedules Steel making Strip Structural steels Thickness Bending force Genetic algorithm (GA) Artificial neural network (ANN) Hot strip rolling
ISSN:	0268-3768, 1433-3015
Online-Zugang:	Volltext
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