| Chaotic time series prediction based on a novel robust echo state network D Li, M Han, J Wang IEEE Transactions on Neural Networks and Learning Systems 23 (5), 787-799, 2012 | 373 | 2012 |
| Support vector echo-state machine for chaotic time-series prediction Z Shi, M Han IEEE transactions on neural networks 18 (2), 359-372, 2007 | 337 | 2007 |
| Prediction of chaotic time series based on the recurrent predictor neural network M Han, J Xi, S Xu, FL Yin IEEE transactions on signal processing 52 (12), 3409-3416, 2004 | 324 | 2004 |
| Output-feedback cooperative formation maneuvering of autonomous surface vehicles with connectivity preservation and collision avoidance Z Peng, D Wang, T Li, M Han IEEE transactions on cybernetics 50 (6), 2527-2535, 2019 | 316 | 2019 |
| Online sequential extreme learning machine with kernels for nonstationary time series prediction X Wang, M Han Neurocomputing 145, 90-97, 2014 | 224 | 2014 |
| Recurrent broad learning systems for time series prediction M Xu, M Han, CLP Chen, T Qiu IEEE transactions on cybernetics 50 (4), 1405-1417, 2018 | 223 | 2018 |
| A review on intelligence dehazing and color restoration for underwater images M Han, Z Lyu, T Qiu, M Xu IEEE Transactions on Systems, Man, and Cybernetics: Systems 50 (5), 1820-1832, 2018 | 206 | 2018 |
| BitTableFI: An efficient mining frequent itemsets algorithm J Dong, M Han Knowledge-Based Systems 20 (4), 329-335, 2007 | 172 | 2007 |
| Single point iterative weighted fuzzy C-means clustering algorithm for remote sensing image segmentation J Fan, M Han, J Wang Pattern Recognition 42 (11), 2527-2540, 2009 | 170 | 2009 |
| Noise smoothing for nonlinear time series using wavelet soft threshold M Han, Y Liu, J Xi, W Guo IEEE signal processing letters 14 (1), 62-65, 2006 | 164 | 2006 |
| Generalized single-hidden layer feedforward networks for regression problems N Wang, MJ Er, M Han IEEE transactions on neural networks and learning systems 26 (6), 1161-1176, 2014 | 140 | 2014 |
| Data-driven based fault prognosis for industrial systems: A concise overview K Zhong, M Han, B Han IEEE/CAA Journal of Automatica Sinica 7 (2), 330-345, 2019 | 136 | 2019 |
| Structured manifold broad learning system: A manifold perspective for large-scale chaotic time series analysis and prediction M Han, S Feng, CLP Chen, M Xu, T Qiu IEEE Transactions on Knowledge and Data Engineering 31 (9), 1809-1821, 2018 | 131 | 2018 |
| Backpropagating constraints-based trajectory tracking control of a quadrotor with constrained actuator dynamics and complex unknowns N Wang, SF Su, M Han, WH Chen IEEE Transactions on Systems, Man, and Cybernetics: Systems 49 (7), 1322-1337, 2018 | 131 | 2018 |
| Parsimonious extreme learning machine using recursive orthogonal least squares N Wang, MJ Er, M Han IEEE transactions on neural networks and learning systems 25 (10), 1828-1841, 2014 | 122 | 2014 |
| Laplacian echo state network for multivariate time series prediction M Han, M Xu IEEE transactions on neural networks and learning systems 29 (1), 238-244, 2017 | 121 | 2017 |
| Adaptive elastic echo state network for multivariate time series prediction M Xu, M Han IEEE transactions on cybernetics 46 (10), 2173-2183, 2016 | 120 | 2016 |
| Interval type-2 fuzzy neural networks for chaotic time series prediction: A concise overview M Han, K Zhong, T Qiu, B Han IEEE transactions on cybernetics 49 (7), 2720-2731, 2018 | 107 | 2018 |
| Multivariate chaotic time series online prediction based on improved kernel recursive least squares algorithm M Han, S Zhang, M Xu, T Qiu, N Wang IEEE transactions on cybernetics 49 (4), 1160-1172, 2018 | 105 | 2018 |
| Analysis and modeling of multivariate chaotic time series based on neural network M Han, Y Wang Expert Systems with Applications 36 (2), 1280-1290, 2009 | 101 | 2009 |
Ning WangSchool of Marine Engineering, Dalian Maritime UniversityVerified email at dlmu.edu.cn
