Haibo He
Cited by
Cited by
Learning from imbalanced data
H He, EA Garcia
IEEE Transactions on knowledge and data engineering 21 (9), 1263-1284, 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
Imbalanced learning: foundations, algorithms, and applications
H He, Y Ma
John Wiley & Sons, 2013
Multiscale convolutional neural networks for fault diagnosis of wind turbine gearbox
G Jiang, H He, J Yan, P Xie
IEEE Transactions on Industrial Electronics 66 (4), 3196-3207, 2018
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
Model-free real-time EV charging scheduling based on deep reinforcement learning
Z Wan, H Li, H He, D Prokhorov
IEEE Transactions on Smart Grid 10 (5), 5246-5257, 2018
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, 1-6, 2015
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
Contribution of the compass satellite navigation system to global PNT users
YX Yang, JL Li, JY Xu, J Tang, HR Guo, HB He
Chinese science bulletin 56, 2813-2819, 2011
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
Adaptive critic nonlinear robust control: A survey
D Wang, H He, D Liu
IEEE transactions on cybernetics 47 (10), 3429-3451, 2017
Dynamic path planning for autonomous driving on various roads with avoidance of static and moving obstacles
X Hu, L Chen, B Tang, D Cao, H He
Mechanical systems and signal processing 100, 482-500, 2018
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
Constrained EV charging scheduling based on safe deep reinforcement learning
H Li, Z Wan, H He
IEEE Transactions on Smart Grid 11 (3), 2427-2439, 2019
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
A local density-based approach for outlier detection
B Tang, H He
Neurocomputing 241, 171-180, 2017
Stacked multilevel-denoising autoencoders: A new representation learning approach for wind turbine gearbox fault diagnosis
G Jiang, H He, P Xie, Y Tang
IEEE Transactions on Instrumentation and Measurement 66 (9), 2391-2402, 2017
Wind turbine fault detection using a denoising autoencoder with temporal information
G Jiang, P Xie, H He, J Yan
IEEE/Asme transactions on mechatronics 23 (1), 89-100, 2017
Stochastic optimization of economic dispatch for microgrid based on approximate dynamic programming
H Shuai, J Fang, X Ai, Y Tang, J Wen, H He
IEEE Transactions on Smart Grid 10 (3), 2440-2452, 2018
Q-learning-based vulnerability analysis of smart grid against sequential topology attacks
J Yan, H He, X Zhong, Y Tang
IEEE Transactions on Information Forensics and Security 12 (1), 200-210, 2016
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