| no |
title |
author |
magazine |
year |
volume |
issue |
page(s) |
type |
| 1 |
An improved defect recognition framework for casting based on DETR algorithm
|
Zhang, Long
|
|
|
30 |
5 |
p. 949-959
|
article
|
| 2 |
An online BOF terminal temperature control model based on big data learning
|
Guo, Jia-wei
|
|
|
30 |
5 |
p. 875-886
|
article
|
| 3 |
An optimization of harmonic structure nickel-saving cryogenic steel via combinatorial high-throughput experiment
|
Jia, Xing-qi
|
|
|
30 |
5 |
p. 1042-1049
|
article
|
| 4 |
A novel mechanism fusion data control method for slab camber in hot rolling
|
Song, Le-bao
|
|
|
30 |
5 |
p. 960-970
|
article
|
| 5 |
A simple image-based method for online moisture content estimation of iron ore green pellets
|
Zhou, Shu-yi
|
|
|
30 |
5 |
p. 851-863
|
article
|
| 6 |
Automatic recognition and intelligent analysis of central shrinkage defects of continuous casting billets based on deep learning
|
Lian, Gong-hao
|
|
|
30 |
5 |
p. 937-948
|
article
|
| 7 |
Cascade model for continuous prediction of silicon content of molten iron with coupled state variable nodes
|
Han, Yang
|
|
|
30 |
5 |
p. 897-914
|
article
|
| 8 |
Data-driven flatness intelligent representation method of cold rolled strip
|
Xu, Yang-huan
|
|
|
30 |
5 |
p. 994-1012
|
article
|
| 9 |
Extended-state-observer-based robust torsional vibration suppression for rolling mill main drive system with input saturation
|
Chen, Jia-qiang
|
|
|
30 |
5 |
p. 985-993
|
article
|
| 10 |
Hot metal quality monitoring system based on big data and machine learning
|
Liu, Ran
|
|
|
30 |
5 |
p. 915-925
|
article
|
| 11 |
Machine learning study on time–temperature–transformation diagram of carbon and low-alloy steel
|
Huang, Xiao-ya
|
|
|
30 |
5 |
p. 1032-1041
|
article
|
| 12 |
Monitoring and diagnosis of complex production process based on free energy of Gaussian–Bernoulli restricted Boltzmann machine
|
Dong, Qian-qian
|
|
|
30 |
5 |
p. 971-984
|
article
|
| 13 |
Multi-model coupling-based dynamic control system of ladle slag in argon blowing refining process
|
Bao, Guang-da
|
|
|
30 |
5 |
p. 926-936
|
article
|
| 14 |
Prediction of blast furnace gas generation based on data quality improvement strategy
|
Liu, Shu-han
|
|
|
30 |
5 |
p. 864-874
|
article
|
| 15 |
Prediction of hot-rolled strip crown based on Boruta and extremely randomized trees algorithms
|
Wang, Li
|
|
|
30 |
5 |
p. 1022-1031
|
article
|
| 16 |
Prior austenite grain boundary recognition in martensite microstructure based on deep learning
|
Wang, Xuan-dong
|
|
|
30 |
5 |
p. 1050-1056
|
article
|
| 17 |
Roll gap prediction in acceleration and deceleration process of cold rolling based on a data-driven method
|
Hu, Yun-jian
|
|
|
30 |
5 |
p. 1013-1021
|
article
|
| 18 |
Special issue on application of AI in steelmaking and ferrous materials
|
Mu, Wangzhong
|
|
|
30 |
5 |
p. 849-850
|
article
|
| 19 |
XGBoost-based model for predicting hydrogen content in electroslag remelting
|
Liu, Yu-xiao
|
|
|
30 |
5 |
p. 887-896
|
article
|
Journal description