Learning from imbalanced data H He, EA Garcia IEEE Transactions on knowledge and data engineering 21 (9), 1263-1284, 2009 | 4471 | 2009 |
ADASYN: Adaptive synthetic sampling approach for imbalanced learning H He, Y Bai, EA Garcia, S Li 2008 IEEE International Joint Conference on Neural Networks (IEEE World …, 2008 | 989 | 2008 |
Adaptively robust filtering for kinematic geodetic positioning Y Yang, H He, G Xu Journal of geodesy 75 (2-3), 109-116, 2001 | 426 | 2001 |
A self-organizing learning array system for power quality classification based on wavelet transform H He, JA Starzyk IEEE Transactions on Power Delivery 21 (1), 286-295, 2005 | 312 | 2005 |
Imbalanced learning: foundations, algorithms, and applications H He, Y Ma John Wiley & Sons, 2013 | 288 | 2013 |
A hierarchical distributed fog computing architecture for big data analysis in smart cities B Tang, Z Chen, G Hefferman, T Wei, H He, Q Yang Proceedings of the ASE BigData & SocialInformatics 2015, 28, 2015 | 177 | 2015 |
Performance assessment of single-and dual-frequency BeiDou/GPS single-epoch kinematic positioning H He, J Li, Y Yang, J Xu, H Guo, A Wang GPS solutions 18 (3), 393-403, 2014 | 169 | 2014 |
A three-network architecture for on-line learning and optimization based on adaptive dynamic programming H He, Z Ni, J Fu Neurocomputing 78 (1), 3-13, 2012 | 169 | 2012 |
Adaptive learning in tracking control based on the dual critic network design Z Ni, H He, J Wen IEEE transactions on neural networks and learning systems 24 (6), 913-928, 2013 | 143 | 2013 |
Air-breathing hypersonic vehicle tracking control based on adaptive dynamic programming C Mu, Z Ni, C Sun, H He IEEE transactions on neural networks and learning systems 28 (3), 584-598, 2016 | 137 | 2016 |
RAMOBoost: ranked minority oversampling in boosting S Chen, H He, EA Garcia IEEE Transactions on Neural Networks 21 (10), 1624-1642, 2010 | 137 | 2010 |
Incremental learning from stream data H He, S Chen, K Li, X Xu IEEE Transactions on Neural Networks 22 (12), 1901-1914, 2011 | 133 | 2011 |
Incorporating intelligence in fog computing for big data analysis in smart cities B Tang, Z Chen, G Hefferman, S Pei, T Wei, H He, Q Yang IEEE Transactions on Industrial informatics 13 (5), 2140-2150, 2017 | 118 | 2017 |
Towards incremental learning of nonstationary imbalanced data stream: a multiple selectively recursive approach S Chen, H He Evolving Systems 2 (1), 35-50, 2011 | 118 | 2011 |
Power system stability control for a wind farm based on adaptive dynamic programming Y Tang, H He, J Wen, J Liu IEEE Transactions on Smart Grid 6 (1), 166-177, 2014 | 117 | 2014 |
Home network power-line communication signal processing based on wavelet packet analysis H He, S Cheng, Y Zhang, J Nguimbis IEEE Transactions on Power Delivery 20 (3), 1879-1885, 2005 | 116 | 2005 |
Cascading failure analysis with DC power flow model and transient stability analysis J Yan, Y Tang, H He, Y Sun IEEE Transactions on Power Systems 30 (1), 285-297, 2014 | 115 | 2014 |
Research on synchronization of chaotic delayed neural networks with stochastic perturbation using impulsive control method X Li, S Song Communications in Nonlinear Science and Numerical Simulation 19 (10), 3892-3900, 2014 | 113* | 2014 |
Toward optimal feature selection in naive Bayes for text categorization B Tang, S Kay, H He IEEE transactions on knowledge and data engineering 28 (9), 2508-2521, 2016 | 112 | 2016 |
Cyber-physical attacks and defences in the smart grid: a survey H He, J Yan IET Cyber-Physical Systems: Theory & Applications 1 (1), 13-27, 2016 | 110 | 2016 |