| Survey of real-time processing systems for big data X Liu, N Iftikhar, X Xie Proceedings of the 18th International Database Engineering & Applications …, 2014 | 218 | 2014 |
| A survey on scholarly data: From big data perspective S Khan, X Liu, KA Shakil, M Alam Information Processing & Management 53 (4), 923-944, 2017 | 174 | 2017 |
| Electricity consumer characteristics identification: A federated learning approach Y Wang, IL Bennani, X Liu, M Sun, Y Zhou IEEE Transactions on Smart Grid 12 (4), 3637-3647, 2021 | 170 | 2021 |
| Clustering-based analysis for residential district heating data P Gianniou, X Liu, A Heller, PS Nielsen, C Rode Energy conversion and management 165, 840-850, 2018 | 164 | 2018 |
| Experimental evaluation of model-free reinforcement learning algorithms for continuous HVAC control M Biemann, F Scheller, X Liu, L Huang Applied Energy 298, 117164, 2021 | 151 | 2021 |
| Deep learning based fusion approach for hate speech detection Y Zhou, Y Yang, H Liu, X Liu, N Savage IEEE Access 8, 128923-128929, 2020 | 105 | 2020 |
| A systematic review of data-driven approaches to fault diagnosis and early warning P Jieyang, A Kimmig, W Dongkun, Z Niu, F Zhi, W Jiahai, X Liu, ... Journal of Intelligent Manufacturing 34 (8), 3277-3304, 2023 | 102 | 2023 |
| Smart Meter Data Analytics: Systems, Algorithms and Benchmarking X Liu, L Golab, W Golab, HF Ilyas, S Jin ACM Transaction on Database Systems, 2016 | 92 | 2016 |
| CITIESData: a smart city data management framework X Liu, A Heller, PS Nielsen Knowledge and Information Systems 53, 699-722, 2017 | 84 | 2017 |
| A Hybrid ICT-Solution for Smart Meter Data Analytics X Liu, PS Nielsen Journal of Energy, 2016 | 82 | 2016 |
| ETLMR: a highly scalable dimensional ETL framework based on mapreduce X Liu, C Thomsen, TB Pedersen Data Warehousing and Knowledge Discovery, 96-111, 2011 | 72 | 2011 |
| Regression-based online anomaly detection for smart grid data X Liu, PS Nielsen arXiv preprint arXiv:1606.05781, 2016 | 67 | 2016 |
| A novel deep class-imbalanced semisupervised model for wind turbine blade icing detection X Cheng, F Shi, X Liu, M Zhao, S Chen IEEE Transactions on Neural Networks and Learning Systems 33 (6), 2558-2570, 2021 | 63 | 2021 |
| Scalable prediction-based online anomaly detection for smart meter data X Liu, PS Nielsen Information Systems 77, 34-47, 2018 | 58 | 2018 |
| Benchmarking Smart Meter Data Analytics. X Liu, L Golab, WM Golab, IF Ilyas In Proc. of EDBT 2015, 385-396, 2015 | 58 | 2015 |
| Online anomaly energy consumption detection using lambda architecture X Liu, N Iftikhar, PS Nielsen, A Heller Big Data Analytics and Knowledge Discovery: 18th International Conference …, 2016 | 57 | 2016 |
| Energy data generation with wasserstein deep convolutional generative adversarial networks J Li, Z Chen, L Cheng, X Liu Energy 257, 124694, 2022 | 55 | 2022 |
| Understanding energy demand behaviors through spatio-temporal smart meter data analysis Z Niu, J Wu, X Liu, L Huang, PS Nielsen Energy 226, 120493, 2021 | 47 | 2021 |
| Wind turbine blade icing detection: A federated learning approach X Cheng, F Shi, Y Liu, X Liu, L Huang Energy 254, 124441, 2022 | 44 | 2022 |
| CloudETL: scalable dimensional ETL for hive X Liu, C Thomsen, TB Pedersen Proceedings of the 18th International Database Engineering & Applications …, 2014 | 44 | 2014 |
Per Sieverts NielsenDTU Management EngineeringPatvirtintas el. paštas dtu.dk
