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La bibliographie suivante contient toutes les publications répertoriées dans la base de données qui sont reliées à ce nom en tant qu'auteur, éditeur ou collaborateur.

  1. Lin, Song-Shun / Zheng, Xin-Jiang: Enhancing smart city assessment: an advanced MCDM approach for urban performance evaluation. Dans: Sustainable Cities and Society.

    https://doi.org/10.1016/j.scs.2024.105930

  2. Lin, Song-Shun / Zhou, Annan / Shen, Shui-Long (2024): Multi-status Bayesian network for analyzing collapse risk of excavation construction. Dans: Automation in Construction, v. 158 (février 2024).

    https://doi.org/10.1016/j.autcon.2023.105193

  3. Lin, Song-Shun / Zhou, Annan / Shen, Shui-Long (2023): Optimal construction method evaluation for underground infrastructure construction. Dans: Automation in Construction, v. 152 (août 2023).

    https://doi.org/10.1016/j.autcon.2023.104921

  4. Lin, Song-Shun / Zhang, Ning / Zhou, Annan / Shen, Shui-Long (2022): Risk evaluation of excavation based on fuzzy decision-making model. Dans: Automation in Construction, v. 136 (avril 2022).

    https://doi.org/10.1016/j.autcon.2022.104143

  5. Lin, Song-Shun / Zhang, Ning / Zhou, Annan / Shen, Shui-Long (2022): Time-series prediction of shield movement performance during tunneling based on hybrid model. Dans: Tunnelling and Underground Space Technology, v. 119 (janvier 2022).

    https://doi.org/10.1016/j.tust.2021.104245

  6. Lin, Song-Shun / Shen, Shui-Long / Zhou, Annan / Zhang, Ning (2021): Ensemble model for risk status evaluation of excavation. Dans: Automation in Construction, v. 132 (décembre 2021).

    https://doi.org/10.1016/j.autcon.2021.103943

  7. Lin, Song-Shun / Shen, Shui-Long / Zhang, Ning / Zhou, Annan (2021): Comprehensive environmental impact evaluation for concrete mixing station (CMS) based on improved TOPSIS method. Dans: Sustainable Cities and Society, v. 69 (juin 2021).

    https://doi.org/10.1016/j.scs.2021.102838

  8. Lin, Song-Shun / Shen, Shui-Long / Zhou, Annan / Xu, Ye-Shuang (2021): Risk assessment and management of excavation system based on fuzzy set theory and machine learning methods. Dans: Automation in Construction, v. 122 (février 2021).

    https://doi.org/10.1016/j.autcon.2020.103490

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