Adrian Chong
Zitiert von
Zitiert von
Whole building energy model for HVAC optimal control: A practical framework based on deep reinforcement learning
Z Zhang, A Chong, Y Pan, C Zhang, KP Lam
Energy and Buildings 199, 472-490, 2019
Green and cool roofs’ urban heat island mitigation potential in tropical climate
J Yang, A Pyrgou, A Chong, M Santamouris, D Kolokotsa, SE Lee
Solar Energy 173, 597-609, 2018
Generative adversarial network for fault detection diagnosis of chillers
K Yan, A Chong, Y Mo
Building and Environment 172, 106698, 2020
Calibrating building energy simulation models: A review of the basics to guide future work
A Chong, Y Gu, H Jia
Energy and Buildings 253, 111533, 2021
Guidelines for the Bayesian calibration of building energy models
A Chong, K Menberg
Energy and Buildings 174, 527-547, 2018
A deep reinforcement learning approach to using whole building energy model for hvac optimal control
Z Zhang, A Chong, Y Pan, C Zhang, S Lu, KP Lam
2018 Building Performance Analysis Conference and SimBuild 3, 22-23, 2018
Bayesian calibration of building energy models with large datasets
A Chong, KP Lam, M Pozzi, J Yang
Energy and Buildings 154, 343-355, 2017
Data requirements and performance evaluation of model predictive control in buildings: A modeling perspective
S Zhan, A Chong
Renewable and Sustainable Energy Reviews 142, 110835, 2021
Building categorization revisited: A clustering-based approach to using smart meter data for building energy benchmarking
S Zhan, Z Liu, A Chong, D Yan
Applied energy 269, 114920, 2020
Occupancy prediction using deep learning approaches across multiple space types: A minimum sensing strategy
ZD Tekler, A Chong
Building and Environment 226, 109689, 2022
Performance evaluation of misting fans in hot and humid climate
NH Wong, AZM Chong
Building and Environment 45 (12), 2666-2678, 2010
Building occupancy and energy consumption: Case studies across building types
S Zhan, A Chong
Energy and Built Environment 2 (2), 167-174, 2021
Data-driven predictive control for smart HVAC system in IoT-integrated buildings with time-series forecasting and reinforcement learning
D Zhuang, VJL Gan, ZD Tekler, A Chong, S Tian, X Shi
Applied Energy 338, 120936, 2023
Improving evolutionary algorithm performance for integer type multi-objective building system design optimization
W Xu, A Chong, OT Karaguzel, KP Lam
Energy and Buildings 127, 714-729, 2016
Building occupancy forecasting: A systematical and critical review
Y Jin, D Yan, A Chong, B Dong, J An
Energy and buildings 251, 111345, 2021
Personal thermal comfort models using digital twins: Preference prediction with BIM-extracted spatial–temporal proximity data from Build2Vec
MM Abdelrahman, A Chong, C Miller
Building and Environment 207, 108532, 2022
Continuous-time Bayesian calibration of energy models using BIM and energy data
A Chong, W Xu, S Chao, NT Ngo
Energy and Buildings 194, 177-190, 2019
Occupancy data at different spatial resolutions: Building energy performance and model calibration
A Chong, G Augenbroe, D Yan
Applied Energy 286, 116492, 2021
Occupant behavior modeling methods for resilient building design, operation and policy at urban scale: A review
B Dong, Y Liu, H Fontenot, M Ouf, M Osman, A Chong, S Qin, F Salim, ...
Applied Energy 293, 116856, 2021
A practical deep reinforcement learning framework for multivariate occupant-centric control in buildings
Y Lei, S Zhan, E Ono, Y Peng, Z Zhang, T Hasama, A Chong
Applied Energy 324, 119742, 2022
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