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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. Lu, Hailong / Cui, Xiaoyu / Han, Hua / Fan, Yuqiang / Zhang, Yunqian (2021): A feature importance ranking based fault diagnosis method for variable-speed screw chiller. In: Science and Technology for the Built Environment, v. 28, n. 2 (December 2021).

    https://doi.org/10.1080/23744731.2021.1993454

  2. Ren, Zhengxiong / Han, Hua / Cui, Xiaoyu / Qing, Hong / Ye, Huiyun (2021): Application of PSO-LSSVM and hybrid programming to fault diagnosis of refrigeration systems. In: Science and Technology for the Built Environment, v. 27, n. 5 (April 2021).

    https://doi.org/10.1080/23744731.2020.1859933

  3. Fan, Yuqiang / Cui, Xiaoyu / Han, Hua / Lu, Hailong (2020): Chiller fault detection and diagnosis by knowledge transfer based on adaptive imbalanced processing. In: Science and Technology for the Built Environment, v. 26, n. 8 (July 2020).

    https://doi.org/10.1080/23744731.2020.1757327

  4. Liang, Qingqing / Han, Hua / Cui, Xiaoyu / Qing, Hong / Fan, Yuqiang (2018): Comparative study of probabilistic neural network and back propagation network for fault diagnosis of refrigeration systems. In: Science and Technology for the Built Environment, v. 24, n. 4 (March 2018).

    https://doi.org/10.1080/23744731.2017.1375012

  5. Gao, Jiaqing / Han, Hua / Ren, Zhengxiong / Fan, Yuqiang (2021): Fault diagnosis for building chillers based on data self-production and deep convolutional neural network. In: Journal of Building Engineering, v. 34 (February 2021).

    https://doi.org/10.1016/j.jobe.2020.102043

  6. Han, Hua / Gu, Bo / Hong, Yingchun / Kang, Jia (2011): Automated FDD of multiple-simultaneous faults (MSF) and the application to building chillers. In: Energy and Buildings, v. 43, n. 9 (September 2011).

    https://doi.org/10.1016/j.enbuild.2011.06.011

  7. Han, Hua / Zhang, Zhan / Cui, Xiaoyu / Meng, Qinghong (2020): Ensemble learning with member optimization for fault diagnosis of a building energy system. In: Energy and Buildings, v. 226 (November 2020).

    https://doi.org/10.1016/j.enbuild.2020.110351

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