Artiklar med krav på offentlig åtkomst - Yang ZhaoLäs mer
Inte tillgängliga någonstans: 43
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
Krav: National Natural Science Foundation of China
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
Krav: National Natural Science Foundation of China
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
Krav: Research Grants Council, Hong Kong
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
Krav: National Natural Science Foundation of China
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
Krav: Research Grants Council, Hong Kong
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
Krav: Research Grants Council, Hong Kong
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
Krav: Research Grants Council, Hong Kong
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
Krav: Research Grants Council, Hong Kong
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
Krav: National Natural Science Foundation of China
A hybrid deep learning-based method for short-term building energy load prediction combined with an interpretation process
C Zhang, J Li, Y Zhao, T Li, Q Chen, X Zhang
Energy and Buildings 225, 110301, 2020
Krav: National Natural Science Foundation of China
A knowledge-guided and data-driven method for building HVAC systems fault diagnosis
T Li, Y Zhao, C Zhang, J Luo, X Zhang
Building and Environment 198, 107850, 2021
Krav: National Natural Science Foundation of China
An improved association rule mining-based method for revealing operational problems of building heating, ventilation and air conditioning (HVAC) systems
C Zhang, X Xue, Y Zhao, X Zhang, T Li
Applied Energy 253, 113492, 2019
Krav: National Natural Science Foundation of China
A study on occupant behaviour related to air-conditioning usage in residential buildings
D Xia, S Lou, Y Huang, Y Zhao, DHW Li, X Zhou
Energy and Buildings 203, 109446, 2019
Krav: National Natural Science Foundation of China
A generic prediction interval estimation method for quantifying the uncertainties in ultra-short-term building cooling load prediction
C Zhang, Y Zhao, C Fan, T Li, X Zhang, J Li
Applied Thermal Engineering 173, 115261, 2020
Krav: National Natural Science Foundation of China
Federated learning-based short-term building energy consumption prediction method for solving the data silos problem
J Li, C Zhang, Y Zhao, W Qiu, Q Chen, X Zhang
Building Simulation 15 (6), 1145-1159, 2022
Krav: National Natural Science Foundation of China
Problem of data imbalance in building energy load prediction: Concept, influence, and solution
C Zhang, J Li, Y Zhao, T Li, Q Chen, X Zhang, W Qiu
Applied Energy 297, 117139, 2021
Krav: National Natural Science Foundation of China
A hierarchical object oriented Bayesian network-based fault diagnosis method for building energy systems
T Li, Y Zhou, Y Zhao, C Zhang, X Zhang
Applied Energy 306, 118088, 2022
Krav: National Natural Science Foundation of China
Homecare-oriented intelligent long-term monitoring of blood pressure using electrocardiogram signals
X Fan, H Wang, F Xu, Y Zhao, KL Tsui
IEEE Transactions on Industrial Informatics 16 (11), 7150-7158, 2019
Krav: National Natural Science Foundation of China
A proactive fault detection and diagnosis method for variable-air-volume terminals in building air conditioning systems
Y Zhao, T Li, C Fan, J Lu, X Zhang, C Zhang, S Chen
Energy and Buildings 183, 527-537, 2019
Krav: National Natural Science Foundation of China
A semantic model-based fault detection approach for building energy systems
T Li, Y Zhao, C Zhang, K Zhou, X Zhang
Building and Environment 207, 108548, 2022
Krav: National Natural Science Foundation of China
Publikations- och finansieringsuppgifter tas fram automatiskt av ett datorprogram.