0
  • DE
  • EN
  • FR
  • International Database and Gallery of Structures

Advertisement

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. Xue, Wenping / Zhang, Guangfa / Chen, Lei / Li, Kangji (2024): Developing a novel personal thermoelectric comfort system for improving indoor occupant’s thermal comfort. In: Journal of Building Engineering, v. 84 (May 2024).

    https://doi.org/10.1016/j.jobe.2024.108561

  2. Li, Kangji / Liu, Yufei / Chen, Lei / Xue, Wenping (2024): Data efficient indoor thermal comfort prediction using instance based transfer learning method. In: Energy and Buildings, v. 306 (March 2024).

    https://doi.org/10.1016/j.enbuild.2024.113920

  3. Wei, Borui / Li, Kangji / Zhou, Shiyi / Xue, Wenping / Tan, Gang (2024): An instance based multi-source transfer learning strategy for building’s short-term electricity loads prediction under sparse data scenarios. In: Journal of Building Engineering, v. 85 (May 2024).

    https://doi.org/10.1016/j.jobe.2024.108713

  4. Li, Kangji / Li, Weiwei / Liu, Fukang / Xue, Wenping (2023): Non-invasive human thermal comfort assessment based on multiple angle/distance facial key-region temperatures recognition. In: Building and Environment, v. 246 (December 2023).

    https://doi.org/10.1016/j.buildenv.2023.110956

  5. Li, Kangji / Zheng, Wen / Xue, Wenping / Wang, Zifeng (2023): Fast reconstruction of indoor temperature field for large-space building based on limited sensors: An experimental study. In: Energy and Buildings, v. 298 (November 2023).

    https://doi.org/10.1016/j.enbuild.2023.113493

  6. Li, Kangji / Yu, Rui / Liu, Yufei / Wang, Junqiang / Xue, Wenping (2023): Correlation analysis and modeling of human thermal sensation with multiple physiological markers: An experimental study. In: Energy and Buildings, v. 278 (January 2023).

    https://doi.org/10.1016/j.enbuild.2022.112643

  7. Li, Kangji / Zhang, Jinxing / Chen, Xu / Xue, Wenping (2022): Building’s hourly electrical load prediction based on data clustering and ensemble learning strategy. In: Energy and Buildings, v. 261 (April 2022).

    https://doi.org/10.1016/j.enbuild.2022.111943

  8. Tian, Jing / Li, Kangji / Xue, Wenping (2021): An adaptive ensemble predictive strategy for multiple scale electrical energy usages forecasting. In: Sustainable Cities and Society, v. 66 (March 2021).

    https://doi.org/10.1016/j.scs.2020.102654

  9. Li, Kangji / Xue, Wenping / Tan, Gang / Denzer, Anthony S. (2019): A state of the art review on the prediction of building energy consumption using data-driven technique and evolutionary algorithms. In: Building Services Engineering Research and Technology, v. 41, n. 1 (December 2019).

    https://doi.org/10.1177/0143624419843647

  10. Li, Kangji / Tian, Jing / Xue, Wenping / Tan, Gang (2021): Short-term electricity consumption prediction for buildings using data-driven swarm intelligence based ensemble model. In: Energy and Buildings, v. 231 (January 2021).

    https://doi.org/10.1016/j.enbuild.2020.110558

  11. Li, Kangji / Xue, Wenping / Xu, Chao / Su, Hongye (2013): Optimization of ventilation system operation in office environment using POD model reduction and genetic algorithm. In: Energy and Buildings, v. 67 (December 2013).

    https://doi.org/10.1016/j.enbuild.2013.07.075

  12. Li, Kangji / Hu, Chenglei / Liu, Guohai / Xue, Wenping (2015): Building's electricity consumption prediction using optimized artificial neural networks and principal component analysis. In: Energy and Buildings, v. 108 (December 2015).

    https://doi.org/10.1016/j.enbuild.2015.09.002

  13. Li, Kangji / Xie, Xianming / Xue, Wenping / Dai, Xiaoli / Chen, Xu / Yang, Xinyun (2018): A hybrid teaching-learning artificial neural network for building electrical energy consumption prediction. In: Energy and Buildings, v. 174 (September 2018).

    https://doi.org/10.1016/j.enbuild.2018.06.017

Search for a publication...

Only available with
My Structurae

Full text
Structurae cooperates with
International Association for Bridge and Structural Engineering (IABSE)
e-mosty Magazine
e-BrIM Magazine