| A short-term building cooling load prediction method using deep learning algorithms C Fan, F Xiao, Y Zhao Applied energy 195, 222-233, 2017 | 634 | 2017 |
| Artificial intelligence-based fault detection and diagnosis methods for building energy systems: Advantages, challenges and the future Y Zhao, T Li, X Zhang, C Zhang Renewable and Sustainable Energy Reviews 109, 85-101, 2019 | 488 | 2019 |
| Occupancy measurement in commercial office buildings for demand-driven control applications—A survey and detection system evaluation T Labeodan, W Zeiler, G Boxem, Y Zhao Energy and Buildings 93, 303-314, 2015 | 392 | 2015 |
| Fault and defect diagnosis of battery for electric vehicles based on big data analysis methods Y Zhao, P Liu, Z Wang, L Zhang, J Hong Applied Energy 207, 354-362, 2017 | 322 | 2017 |
| Pattern recognition-based chillers fault detection method using Support Vector Data Description (SVDD) Y Zhao, S Wang, F Xiao Applied Energy 112, 1041-1048, 2013 | 276 | 2013 |
| Analytical investigation of autoencoder-based methods for unsupervised anomaly detection in building energy data C Fan, F Xiao, Y Zhao, J Wang Applied energy 211, 1123-1135, 2018 | 271 | 2018 |
| A review of data mining technologies in building energy systems: Load prediction, pattern identification, fault detection and diagnosis Y Zhao, C Zhang, Y Zhang, Z Wang, J Li Energy and Built Environment 1 (2), 149-164, 2020 | 258 | 2020 |
| Deep learning-based feature engineering methods for improved building energy prediction C Fan, Y Sun, Y Zhao, M Song, J Wang Applied energy 240, 35-45, 2019 | 256 | 2019 |
| An intelligent chiller fault detection and diagnosis methodology using Bayesian belief network Y Zhao, F Xiao, S Wang Energy and Buildings 57, 278-288, 2013 | 234 | 2013 |
| Renewable energy system optimization of low/zero energy buildings using single-objective and multi-objective optimization methods Y Lu, S Wang, Y Zhao, C Yan Energy and Buildings 89, 61–75, 2015 | 223 | 2015 |
| MPC-Based Optimal Scheduling of Grid-Connected Low Energy Buildings with Thermal Energy Storages Y Zhao, Y Lu, C Yan, S Wang Energy and Buildings, http://www.sciencedirect.com/science/art, 2014 | 193 | 2014 |
| Diagnostic Bayesian networks for diagnosing air handling units faults–part I: Faults in dampers, fans, filters and sensors Y Zhao, J Wen, F Xiao, X Yang, S Wang Applied Thermal Engineering 111, 1272-1286, 2017 | 185 | 2017 |
| Demand side flexibility: Potentials and building performance implications KO Aduda, T Labeodan, W Zeiler, G Boxem, Y Zhao Sustainable cities and society 22, 146-163, 2016 | 174 | 2016 |
| A decision tree based data-driven diagnostic strategy for air handling units R Yan, Z Ma, Y Zhao, G Kokogiannakis Energy and Buildings 133, 37-45, 2016 | 162 | 2016 |
| Bayesian network based FDD strategy for variable air volume terminals F Xiao, Y Zhao, J Wen, S Wang Automation in Construction 41, 106-118, 2014 | 151 | 2014 |
| Diagnostic Bayesian networks for diagnosing air handling units faults – Part II: Faults in coils and sensors Y Zhao, J Wen, S Wang Applied Thermal Engineering 90 (5), 145–157, 2015 | 144 | 2015 |
| A statistical fault detection and diagnosis method for centrifugal chillers based on exponentially-weighted moving average control charts and support vector regression Y Zhao, S Wang, F Xiao Applied Thermal Engineering 51 (1-2), 560-572, 2013 | 144 | 2013 |
| Virtual occupancy sensors for real-time occupancy information in buildings Y Zhao, W Zeiler, G Boxem, T Labeodan Building and Environment 93 (2), 9–20, 2015 | 105 | 2015 |
| Optimal design and application of a compound cold storage system combining seasonal ice storage and chilled water storage C Yan, W Shi, X Li, Y Zhao Applied Energy 171, 1-11, 2016 | 101 | 2016 |
| A sensor fault detection strategy for air handling units using cluster analysis R Yan, Z Ma, G Kokogiannakis, Y Zhao Automation in Construction 70, 77-88, 2016 | 99 | 2016 |
XIAO, Fu LindaDepartment of Building Environment and Energy Engineering, The Hong Kong Polytechnic University在 polyu.edu.hk 的电子邮件经过验证
