International Journal of Control, Automation and Systems 2017; 15(3): 1466-1477
Published online May 22, 2017
https://doi.org/10.1007/s12555-015-0463-7
© The International Journal of Control, Automation, and Systems
The elongation of steel-strips in annealing furnace is an important factor that affects the position of welding line and safety of air-knife since there is no extra space to install welding line detector in field conditions. Therefore, predicting the elongation of steel-strips in the annealing process is important to fulfill the requirements of eliminating security risks and improving economic performance. In this paper, we propose a deep architectures called I-ELM/MLCSA autoencoders with the concept of stacked generalization philosophy to solve large and complex data mining problems. The comparison results of the case studies indicate that D-ELMs-AE/MLCSA is a promising prediction algorithm and can be employed for steel-strips elongation predictions with excellent performance."
Keywords Baldwinian learning, Clone selection algorithm, deep learning, elongation prediction, incremental extreme learning machine, Lamarckian learning.
International Journal of Control, Automation and Systems 2017; 15(3): 1466-1477
Published online June 1, 2017 https://doi.org/10.1007/s12555-015-0463-7
Copyright © The International Journal of Control, Automation, and Systems.
Chao Wang*, Jian-HuiWang, Shu-Sheng Gu, XiaoWang, and Yu-Xian Zhang
Northeastern University
The elongation of steel-strips in annealing furnace is an important factor that affects the position of welding line and safety of air-knife since there is no extra space to install welding line detector in field conditions. Therefore, predicting the elongation of steel-strips in the annealing process is important to fulfill the requirements of eliminating security risks and improving economic performance. In this paper, we propose a deep architectures called I-ELM/MLCSA autoencoders with the concept of stacked generalization philosophy to solve large and complex data mining problems. The comparison results of the case studies indicate that D-ELMs-AE/MLCSA is a promising prediction algorithm and can be employed for steel-strips elongation predictions with excellent performance."
Keywords: Baldwinian learning, Clone selection algorithm, deep learning, elongation prediction, incremental extreme learning machine, Lamarckian learning.
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