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Cheng Fan
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Year
A short-term building cooling load prediction method using deep learning algorithms
C Fan, F Xiao, Y Zhao
Applied energy 195, 222-233, 2017
6072017
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
5762014
Data mining in building automation system for improving building operational performance
F Xiao, C Fan
Energy and buildings 75, 109-118, 2014
2992014
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
2732019
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
2502018
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
2442019
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
2422015
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
2142018
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
1972021
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
1642020
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
1602015
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
1532021
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
1292019
Attention-based interpretable neural network for building cooling load prediction
A Li, F Xiao, C Zhang, C Fan
Applied Energy 299, 117238, 2021
1242021
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
952018
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
872019
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
852016
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
792021
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
762021
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
602018
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