Zobrazeno 1 - 10
of 101
pro vyhledávání: '"Zhuang, Chaoqun"'
Autor:
Langtry, Max, Zhuang, Chaoqun, Ward, Rebecca, Makasis, Nikolas, Kreitmair, Monika J., Conti, Zack Xuereb, Di Francesco, Domenic, Choudhary, Ruchi
The use of data collection to support decision making through the reduction of uncertainty is ubiquitous in the management, operation, and design of building energy systems. However, no existing studies in the building energy systems literature have
Externí odkaz:
http://arxiv.org/abs/2409.00049
Autor:
Langtry, Max, Wichitwechkarn, Vijja, Ward, Rebecca, Zhuang, Chaoqun, Kreitmair, Monika J., Makasis, Nikolas, Conti, Zack Xuereb, Choudhary, Ruchi
Publikováno v:
Energy and Buildings (2024)
Data is required to develop forecasting models for use in Model Predictive Control (MPC) schemes in building energy systems. However, data is costly to both collect and exploit. Determining cost optimal data usage strategies requires understanding of
Externí odkaz:
http://arxiv.org/abs/2402.12539
Low-light hazy scenes commonly appear at dusk and early morning. The visual enhancement for low-light hazy images is an ill-posed problem. Even though numerous methods have been proposed for image dehazing and low-light enhancement respectively, simp
Externí odkaz:
http://arxiv.org/abs/2308.00591
Autor:
Langtry, Max, Zhuang, Chaoqun, Ward, Rebecca, Makasis, Nikolas, Kreitmair, Monika J., Conti, Zack Xuereb, Di Francesco, Domenic, Choudhary, Ruchi
The use of monitored data to improve the accuracy of building energy models and operation of energy systems is ubiquitous, with topics such as building monitoring and Digital Twinning attracting substantial research attention. However, little attenti
Externí odkaz:
http://arxiv.org/abs/2305.16117
Autor:
Guo, Rui, Min, Yunran, Gao, Yafeng, Chen, Xiangjie, Shi, Huizhong, Liu, Changqiao, Zhuang, Chaoqun
Publikováno v:
In Building and Environment 1 August 2024 261
Publikováno v:
In Energy 15 April 2024 293
Autor:
Dong, Shiqian, Long, He, Guan, Jingxuan, Jiang, Lina, Zhuang, Chaoqun, Gao, Yafeng, Di, Yanqiang
Publikováno v:
In Energy 1 February 2024 288
Anomaly detection from a single image is challenging since anomaly data is always rare and can be with highly unpredictable types. With only anomaly-free data available, most existing methods train an AutoEncoder to reconstruct the input image and fi
Externí odkaz:
http://arxiv.org/abs/2103.11671
Autor:
Jiang, Lina, Gao, Yafeng, Zhuang, Chaoqun, Feng, Chi, Zhang, Xiaotong, Guan, Jingxuan, Dong, Shiqian
Publikováno v:
In Sustainable Cities and Society December 2023 99
Publikováno v:
In Applied Energy 1 July 2023 341