| Short-term load forecasting with deep residual networks K Chen, K Chen, Q Wang, Z He, J Hu, J He IEEE Transactions on Smart Grid 10 (4), 3943-3952, 2018 | 608 | 2018 |
| Convolutional sequence to sequence non‐intrusive load monitoring K Chen, Q Wang, Z He, K Chen, J Hu, J He the Journal of Engineering 2018 (17), 1860-1864, 2018 | 102 | 2018 |
| A novel data-driven approach for residential electricity consumption prediction based on ensemble learning K Chen, J Jiang, F Zheng, K Chen Energy 150, 49-60, 2018 | 61 | 2018 |
| Solar energy forecasting with numerical weather predictions on a grid and convolutional networks K Chen, Z He, K Chen, J Hu, J He 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2), 1-5, 2017 | 26 | 2017 |
| Practical failure recognition model of lithium-ion batteries based on partial charging process K Chen, F Zheng, J Jiang, W Zhang, Y Jiang, K Chen Energy 138, 1199-1208, 2017 | 25 | 2017 |
| GP-NAS-ensemble: a model for NAS Performance Prediction K Chen, L Yang, Y Chen, K Chen, Y Xu, L Li arXiv preprint arXiv:2301.09231, 2023 | 14 | 2023 |
| SOH estimation for lithium-ion batteries: A cointegration and error correction approach C Kunlong, J Jiuchun, Z Fangdan, S Bingxiang, Z Yanru 2016 IEEE International Conference on Prognostics and Health Management …, 2016 | 13 | 2016 |
| Peak power prediction model for batteries based on data statistical characteristic and GS-SVM Z Fangdan, J Jiuchun, C Kunlong Electric Power Automation Equipment 37 (9), 56-61, 2017 | 8 | 2017 |
| DQN Control Solution for KDD Cup 2021 City Brain Challenge Y Chen, K Chen, K Chen, L Wang arXiv preprint arXiv:2108.06491, 2021 | | 2021 |
