| Modeling and Forecasting Short-Term Power Load With Copula Model and Deep Belief Network T Ouyang, Y He, H Li, Z Sun, S Baek IEEE Transactions on Emerging Topics in Computational Intelligence 3 (2 …, 2019 | 196* | 2019 |
| Modeling wind-turbine power curve: A data partitioning and mining approach T Ouyang, A Kusiak, Y He Renewable Energy 102, 1-8, 2017 | 185 | 2017 |
| Distribution and failure modes of the landslides in Heitai terrace, China D Peng, Q Xu, F Liu, Y He, S Zhang, X Qi, K Zhao, X Zhang Engineering Geology 236, 97-110, 2018 | 140 | 2018 |
| Prediction of landslide displacement with an ensemble-based extreme learning machine and copula models H Li, Q Xu, Y He, J Deng Landslides 15, 2047-2059, 2018 | 110 | 2018 |
| Detection and segmentation of loess landslides via satellite images: A two-phase framework H Li, Y He, Q Xu, J Deng, W Li, Y Wei Landslides 19 (3), 673-686, 2022 | 107 | 2022 |
| Deep segmentation networks predict survival of non-small cell lung cancer S Baek, Y He, BG Allen, JM Buatti, BJ Smith, L Tong, Z Sun, J Wu, ... Scientific reports 9, 2019 | 92 | 2019 |
| Performance assessment of wind turbines: Data-derived quantitative metrics Y He, A Kusiak IEEE Transactions on Sustainable Energy 9 (1), 65-73, 2017 | 92 | 2017 |
| Short-term power load forecasting with deep belief network and copula models Y He, J Deng, H Li 2017 9th International conference on intelligent human-machine systems and …, 2017 | 79 | 2017 |
| Modeling and predicting reservoir landslide displacement with deep belief network and EWMA control charts: a case study in Three Gorges Reservoir H Li, Q Xu, Y He, X Fan, S Li Landslides 17 (3), 693-707, 2020 | 75 | 2020 |
| Chaotic wind power time series prediction via switching data-driven modes T Ouyang, H Huang, Y He, Z Tang Renewable Energy 145, 270-281, 2020 | 75 | 2020 |
| Predictive model of yaw error in a wind turbine T Ouyang, A Kusiak, Y He Energy 123, 119-130, 2017 | 71 | 2017 |
| Comparison of data-driven models of loess landslide runout distance estimation Q Xu, H Li, Y He, F Liu, D Peng Bulletin of Engineering Geology and the Environment 78, 1281-1294, 2019 | 62 | 2019 |
| Prediction of wind power ramp events based on residual correction T Ouyang, X Zha, L Qin, Y He, Z Tang Renewable energy 136, 781-792, 2019 | 60 | 2019 |
| Predictive modeling of landslide displacement by wavelet analysis and multiple extreme learning machines H Li, Q Xu, Y He, Y Wei Journal of Engineering Geology 24 (5), 721-731, 2016 | 28* | 2016 |
| Monitoring wind turbines' unhealthy status: a data-driven approach T Ouyang, Y He, H Huang IEEE Transactions on Emerging Topics in Computational Intelligence 3 (2 …, 2018 | 27 | 2018 |
| Zernet: Convolutional neural networks on arbitrary surfaces via zernike local tangent space estimation Z Sun, E Rooke, J Charton, Y He, J Lu, S Baek Computer Graphics Forum 39 (6), 204-216, 2020 | 26 | 2020 |
| Data-driven modeling of truck engine exhaust valve failures: a case study Y He, A Kusiak, T Ouyang, W Teng Journal of mechanical science and technology 31, 2747-2757, 2017 | 26 | 2017 |
| Ramp events forecasting based on long‐term wind power prediction and correction T Ouyang, H Huang, Y He IET Renewable Power Generation 13 (15), 2793-2801, 2019 | 25 | 2019 |
| Embedded spectral descriptors: learning the point-wise correspondence metric via Siamese neural networks Z Sun, Y He, A Gritsenko, A Lendasse, S Baek Journal of Computational Design and Engineering 7 (1), 18-29, 2020 | 17 | 2020 |
| Deep spectral descriptors: learning the point-wise correspondence metric via Siamese deep neural networks Z Sun, Y He, A Gritsenko, A Lendasse, S Baek arXiv preprint arXiv:1710.06368 2, 2017 | 16 | 2017 |
Stephen BaekAssociate Professor, University of VirginiaGeverifieerd e-mailadres voor virginia.edu
