| 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 |
| Development of prediction models for next-day building energy consumption and peak power demand using data mining techniques C Fan, F Xiao, S Wang Applied Energy 127, 1-10, 2014 | 595 | 2014 |
| Data mining in building automation system for improving building operational performance F Xiao, C Fan Energy and buildings 75, 109-118, 2014 | 307 | 2014 |
| Assessment of deep recurrent neural network-based strategies for short-term building energy predictions C Fan, J Wang, W Gang, S Li Applied energy 236, 700-710, 2019 | 305 | 2019 |
| 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 |
| 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 |
| A framework for knowledge discovery in massive building automation data and its application in building diagnostics C Fan, F Xiao, C Yan Automation in Construction 50, 81-90, 2015 | 248 | 2015 |
| A review on data preprocessing techniques toward efficient and reliable knowledge discovery from building operational data C Fan, M Chen, X Wang, J Wang, B Huang Frontiers in energy research 9, 652801, 2021 | 243 | 2021 |
| Unsupervised data analytics in mining big building operational data for energy efficiency enhancement: A review C Fan, F Xiao, Z Li, J Wang Energy and Buildings 159, 296-308, 2018 | 221 | 2018 |
| Statistical investigations of transfer learning-based methodology for short-term building energy predictions C Fan, Y Sun, F Xiao, J Ma, D Lee, J Wang, YC Tseng Applied Energy 262, 114499, 2020 | 175 | 2020 |
| Temporal knowledge discovery in big BAS data for building energy management C Fan, F Xiao, H Madsen, D Wang Energy and buildings 109, 75-89, 2015 | 167 | 2015 |
| Advanced data analytics for enhancing building performances: From data-driven to big data-driven approaches C Fan, D Yan, F Xiao, A Li, J An, X Kang Building Simulation 14, 3-24, 2021 | 165 | 2021 |
| Attention-based interpretable neural network for building cooling load prediction A Li, F Xiao, C Zhang, C Fan Applied Energy 299, 117238, 2021 | 144 | 2021 |
| A novel methodology to explain and evaluate data-driven building energy performance models based on interpretable machine learning C Fan, F Xiao, C Yan, C Liu, Z Li, J Wang Applied Energy 235, 1551-1560, 2019 | 138 | 2019 |
| A model for simulating schedule risks in prefabrication housing production: A case study of six-day cycle assembly activities in Hong Kong CZ Li, X Xu, GQ Shen, C Fan, X Li, J Hong Journal of cleaner production 185, 366-381, 2018 | 101 | 2018 |
| A hybrid building thermal modeling approach for predicting temperatures in typical, detached, two-story houses B Cui, C Fan, J Munk, N Mao, F Xiao, J Dong, T Kuruganti Applied energy 236, 101-116, 2019 | 94 | 2019 |
| An uncertainty-based design optimization method for district cooling systems W Gang, G Augenbroe, S Wang, C Fan, F Xiao Energy 102, 516-527, 2016 | 88 | 2016 |
| Development of an ANN-based building energy model for information-poor buildings using transfer learning A Li, F Xiao, C Fan, M Hu Building simulation 14, 89-101, 2021 | 85 | 2021 |
| An explainable one-dimensional convolutional neural networks based fault diagnosis method for building heating, ventilation and air conditioning systems G Li, Q Yao, C Fan, C Zhou, G Wu, Z Zhou, X Fang Building and Environment 203, 108057, 2021 | 83 | 2021 |
| Schedule delay analysis of prefabricated housing production: A hybrid dynamic approach CZ Li, J Hong, C Fan, X Xu, GQ Shen Journal of cleaner production 195, 1533-1545, 2018 | 63 | 2018 |
