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The following bibliography contains all publications indexed in this database that are linked with this name as either author, editor or any other kind of contributor.

  1. Zhang, Hanyuan / Yang, Wenxin / Yi, Weilin / Lim, Jit Bing / An, Zenghui / Li, Chengdong (2023): Imbalanced data based fault diagnosis of the chiller via integrating a new resampling technique with an improved ensemble extreme learning machine. In: Journal of Building Engineering, v. 70 (July 2023).

    https://doi.org/10.1016/j.jobe.2023.106338

  2. Jiang, Yongqing / Pang, Dandan / Li, Chengdong / Wang, Jianze (2023): A method of concrete damage detection and localization based on weakly supervised learning. In: Computer-Aided Civil and Infrastructure Engineering, v. 39, n. 7 (November 2023).

    https://doi.org/10.1111/mice.13124

  3. Yu, Yulong / Zhang, Hanyuan / Peng, Wei / Wang, Ruiqi / Li, Chengdong (2022): Images based fault diagnosis of air handling unit via combining kernel slow feature analysis and deep learning method. In: Journal of Building Engineering, v. 56 (September 2022).

    https://doi.org/10.1016/j.jobe.2022.104718

  4. Zhang, Hanyuan / Li, Chengdong / Wei, Qinglai / Zhang, Yunchu (2022): Fault detection and diagnosis of the air handling unit via combining the feature sparse representation based dynamic SFA and the LSTM network. In: Energy and Buildings, v. 269 (August 2022).

    https://doi.org/10.1016/j.enbuild.2022.112241

  5. Tian, Chenlu / Ye, Yunyang / Lou, Yingli / Zuo, Wangda / Zhang, Guiqing / Li, Chengdong (2022): Daily power demand prediction for buildings at a large scale using a hybrid of physics-based model and generative adversarial network. In: Building Simulation, v. 15, n. 9 (February 2022).

    https://doi.org/10.1007/s12273-022-0887-y

  6. Zhang, Hanyuan / Li, Chengdong / Li, Ding / Zhang, Yunchu / Peng, Wei (2021): Fault detection and diagnosis of the air handling unit via an enhanced kernel slow feature analysis approach considering the time-wise and batch-wise dynamics. In: Energy and Buildings, v. 253 (December 2021).

    https://doi.org/10.1016/j.enbuild.2021.111467

  7. Li, Chengdong / Shen, Cunxiao / Zhang, Hanyuan / Sun, Hongchang / Meng, Songping (2021): A novel temporal convolutional network via enhancing feature extraction for the chiller fault diagnosis. In: Journal of Building Engineering, v. 42 (October 2021).

    https://doi.org/10.1016/j.jobe.2021.103014

  8. Jiang, Yongqing / Pang, Dandan / Li, Chengdong (2021): A deep learning approach for fast detection and classification of concrete damage. In: Automation in Construction, v. 128 (August 2021).

    https://doi.org/10.1016/j.autcon.2021.103785

  9. Sun, Jinfeng / Tian, Liang / Yu, Zhuqing / Zhang, Yu / Li, Chengdong / Hou, Guihua / Shen, Xiaodong (2020): Studies on the size effects of nano-TiO2 on Portland cement hydration with different water to solid ratios. In: Construction and Building Materials, v. 259 (October 2020).

    https://doi.org/10.1016/j.conbuildmat.2020.120390

  10. Boafo, Fred Edmond / Chen, Zhaofeng / Li, Chengdong / Li, Binbin / Xu, Tengzhou (2014): Structure of vacuum insulation panel in building system. In: Energy and Buildings, v. 85 (December 2014).

    https://doi.org/10.1016/j.enbuild.2014.06.055

  11. Li, Chengdong / Li, Binbin / Pan, Ning / Chen, Zhaofeng / Saeed, Muhammad Umar / Xu, Tengzhou / Yang, Yong (2016): Thermo-physical properties of polyester fiber reinforced fumed silica/hollow glass microsphere composite core and resulted vacuum insulation panel. In: Energy and Buildings, v. 125 (August 2016).

    https://doi.org/10.1016/j.enbuild.2016.05.013

  12. Li, Ding / Li, Donghui / Li, Chengdong / Li, Lin / Gao, Long (2019): A novel data-temporal attention network based strategy for fault diagnosis of chiller sensors. In: Energy and Buildings, v. 198 (September 2019).

    https://doi.org/10.1016/j.enbuild.2019.06.034

  13. Tian, Chenlu / Li, Chengdong / Zhang, Guiqing / Lv, Yisheng (2019): Data driven parallel prediction of building energy consumption using generative adversarial nets. In: Energy and Buildings, v. 186 (March 2019).

    https://doi.org/10.1016/j.enbuild.2019.01.034

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