Modeling of the thermal state change of blast furnace hearth with support vector machines C Gao, L Jian, S Luo IEEE Transactions on Industrial Electronics 59 (2), 1134-1145, 2012 | 172 | 2012 |
A comparative analysis of support vector machines and extreme learning machines X Liu, C Gao, P Li Neural Networks 33, 58-66, 2012 | 144 | 2012 |
Data-driven time discrete models for dynamic prediction of the hot metal silicon content in the blast furnace—A review H Saxén, C Gao, Z Gao IEEE Transactions on Industrial Informatics 9 (4), 2213-2225, 2013 | 143 | 2013 |
Rule extraction from fuzzy-based blast furnace SVM multiclassifier for decision-making C Gao, Q Ge, L Jian IEEE Transactions on Fuzzy Systems 22 (3), 586-596, 2014 | 84 | 2014 |
复杂高炉炼铁过程的数据驱动建模及预测算法 郜传厚, 渐令, 陈积明, 孙优贤 自动化学报 35 (6), 725-730, 2009 | 76* | 2009 |
Novel just-In-time learning-based soft sensor utilizing non-Gaussian information L Xie, J Zeng, C Gao IEEE Transactions on Control Systems Technology 22 (1), 360-368, 2014 | 75 | 2014 |
Binary coding SVMs for the multiclass problem of blast furnace system L Jian, C Gao IEEE Transactions on Industrial Electronics 60 (9), 3846-3856, 2013 | 74 | 2013 |
Improvement of identification of blast furnace ironmaking process by outlier detection and missing value imputation J Zeng, C Gao Journal of Process Control 19 (9), 1519-1528, 2009 | 71 | 2009 |
Data-driven predictive control for blast furnace ironmaking process J Zeng, C Gao, H Su Computers & Chemical Engineering 34 (11), 1854-1862, 2010 | 69 | 2010 |
Constructing multiple kernel learning framework for blast furnace automation L Jian, C Gao, Z Xia IEEE Transactions on Automation Science and Engineering 9 (4), 763-777, 2012 | 65 | 2012 |
A chaos‐based iterated multistep predictor for blast furnace ironmaking process C Gao, J Chen, J Zeng, X Liu, Y Sun AIChE Journal 55 (4), 947-962, 2009 | 63 | 2009 |
Application of least squares support vector machines to predict the silicon content in blast furnace hot metal L Jian, C Gao, L Li, J Zeng ISIJ International 48 (11), 1659-1661, 2008 | 62 | 2008 |
Guest editorial: Special section on data-driven approaches for complex industrial systems Z Gao, H Saxen, C Gao IEEE Transactions on Industrial Informatics 9 (4), 2210-2212, 2013 | 60 | 2013 |
Data-driven modeling based on volterra series for multidimensional blast furnace system C Gao, L Jian, X Liu, J Chen, Y Sun IEEE Transactions on Neural Networks 22 (12), 2272-2283, 2011 | 49 | 2011 |
Design of a multiple kernel learning algorithm for LS-SVM by convex programming L Jian, Z Xia, X Liang, C Gao Neural Networks 24 (5), 476-483, 2011 | 44 | 2011 |
Fast leave-one-out crossvalidation algorithm for extreme learning machine X Liu, P Li, C Gao Journal of Shanghai Jiaotong University 45 (8), 1140-1145, 2011 | 40 | 2011 |
A sliding‐window smooth support vector regression model for nonlinear blast furnace system L Jian, C Gao, Z Xia Steel Research International 82 (3), 169-179, 2011 | 38 | 2011 |
Linear priors minded and integrated for transparency of blast furnace black-box SVM model S Chen, C Gao IEEE Transactions on Industrial Informatics 16 (6), 3862-3870, 2020 | 35 | 2020 |
Chaotic identification and prediction of silicon content in hot metal C Gao, Z Zhou, J Qian Journal of Iron and Steel Research International 12 (5), 3-5, 2005 | 29 | 2005 |
An optimal control method for applications using wireless sensor/actuator networks X Cao, J Chen, C Gao, Y Sun Computers & Electrical Engineering 35 (5), 748-756, 2009 | 28 | 2009 |