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2023 Vol. 30 No. 05
Published: 24 June 2023
Original Paper
Original paper
851
Shu-yi Zhou, Xiao-yan Liu
A simple image-based method for online moisture content estimation of iron ore green pellets
2023 Vol. 30 (05): 851-863 [
Abstract
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72
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138
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864
Shu-han Liu, Wen-qiang Sun, Wei-dong Li, Bing-zhen Jin
Prediction of blast furnace gas generation based on data quality improvement strategy
2023 Vol. 30 (05): 864-874 [
Abstract
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65
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112
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875
Jia-wei Guo, Dong-ping Zhan, Guo-cai Xu, Nai-hui Yang, Bo Wang, Ming-xin Wang, Geng-wei You
An online BOF terminal temperature control model based on big data learning
2023 Vol. 30 (05): 875-886 [
Abstract
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87
) [
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1KB] [
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138
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897
Yang Han, Ze-qian Cui, Li-jing Wang, Jie Li, Ai-min Yang, Yu-zhu Zhang
Cascade model for continuous prediction of silicon content of molten iron with coupled state variable nodes
2023 Vol. 30 (05): 897-914 [
Abstract
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61
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1KB] [
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119
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915
Ran Liu, Zhi-feng Zhang, Xin Li, Xiao-jie Liu, Hong-yang Li, Xiang-ping Bu, Jun Zhao, Qing Lyu
Hot metal quality monitoring system based on big data and machine learning
2023 Vol. 30 (05): 915-925 [
Abstract
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61
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1KB] [
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129
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926
Guang-da Bao, Ting Wu, Duo-gang Wang, Xiao-bin Zhou, Hai-chuan Wang
Multi-model coupling-based dynamic control system of ladle slag in argon blowing refining process
2023 Vol. 30 (05): 926-936 [
Abstract
] (
56
) [
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1KB] [
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123
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937
Gong-hao Lian, Qi-hao Sun, Xiao-ming Liu, Wei-miao Kong, Ming Lv, Jian-jun Qi, Yong Liu, Ben-ming Yuan, Qiang Wang
Automatic recognition and intelligent analysis of central shrinkage defects of continuous casting billets based on deep learning
2023 Vol. 30 (05): 937-948 [
Abstract
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57
) [
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1KB] [
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139
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949
Long Zhang, Sai-fei Yan, Jun Hong, Qian Xie, Fei Zhou, Song-lin Ran
An improved defect recognition framework for casting based on DETR algorithm
2023 Vol. 30 (05): 949-959 [
Abstract
] (
78
) [
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1KB] [
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0KB] (
135
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960
Le-bao Song, Dong Xu, Peng-fei Liu, Jin-hang Zhou, Hui-qing Yan, Jing-dong Li, Hai-nan He, Hai-jun Yu, Xiao-chen Wang, Quan Yang
A novel mechanism fusion data control method for slab camber in hot rolling
2023 Vol. 30 (05): 960-970 [
Abstract
] (
55
) [
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1KB] [
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128
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971
Qian-qian Dong, Qing-ting Qian, Min Li, Gang Xu
Monitoring and diagnosis of complex production process based on free energy of Gaussian–Bernoulli restricted Boltzmann machine
2023 Vol. 30 (05): 971-984 [
Abstract
] (
38
) [
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1KB] [
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126
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985
Jia-qiang Chen, Shu-zong Chen, Chang-chun Hua, Cheng Jia, Cheng Qian
Extended-state-observer-based robust torsional vibration suppression for rolling mill main drive system with input saturation
2023 Vol. 30 (05): 985-993 [
Abstract
] (
59
) [
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1KB] [
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143
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994
Yang-huan Xu, Dong-cheng Wang, Bo-wei Duan, Hong-min Liu
Data-driven flatness intelligent representation method of cold rolled strip
2023 Vol. 30 (05): 994-1012 [
Abstract
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34
) [
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1KB] [
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125
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1013
Yun-jian Hu, Jie Sun, Huai-tao Shi, Qing-long Wang, Jian-zhao Cao
Roll gap prediction in acceleration and deceleration process of cold rolling based on a data-driven method
2023 Vol. 30 (05): 1013-1021 [
Abstract
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47
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1KB] [
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123
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1022
Li Wang, Song-lin He, Zhi-ting Zhao, Xian-du Zhang
Prediction of hot-rolled strip crown based on Boruta and extremely randomized trees algorithms
2023 Vol. 30 (05): 1022-1031 [
Abstract
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49
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1KB] [
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130
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1032
Xiao-ya Huang, Biao Zhang, Qiang Tian, Hong-hui Wu, Bin Gan, Zhong-nan Bi, Wei-hua Xue, Asad Ullah, Hao Wang
Machine learning study on time–temperature–transformation diagram of carbon and low-alloy steel
2023 Vol. 30 (05): 1032-1041 [
Abstract
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48
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1KB] [
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121
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1042
Xing-qi Jia, Feng-hua Lu, Kai Yang, Shi-long Liu, Chun Yu, Wei Li, Xue-jun Jin
An optimization of harmonic structure nickel-saving cryogenic steel via combinatorial high-throughput experiment
2023 Vol. 30 (05): 1042-1049 [
Abstract
] (
61
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1KB] [
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143
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1050
Xuan-dong Wang, Nan Li, Hang Su, Hui-min Meng
Prior austenite grain boundary recognition in martensite microstructure based on deep learning
2023 Vol. 30 (05): 1050-1056 [
Abstract
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47
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1KB] [
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122
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887
Yu-xiao Liu, Yan-wu Dong, Zhou-hua Jiang, Yu-shuo Li, Wei Zha, Yao-xin Du, Shu-yang Du
XGBoost-based model for predicting hydrogen content in electroslag remelting
2023 Vol. 30 (05): 887-896 [
Abstract
] (
42
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113
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