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Pinsheng Duan

Die folgende Bibliografie enthält alle in dieser Datenbank indizierten Veröffentlichungen, die mit diesem Namen als Autor, Herausgeber oder anderweitig Beitragenden verbunden sind.

  1. Duan, Pinsheng / Zhou, Jianliang / Qiao, Yaning / Guo, Ping (2024): Block-based construction worker trajectory prediction method driven by site risk. In: Automation in Construction, v. 167 (November 2024).

    https://doi.org/10.1016/j.autcon.2024.105721

  2. Duan, Pinsheng / Zhou, Jianliang / Goh, Yang Miang (2023): Safety Risk Diagnosis Based on Motion Trajectory for Construction Workers: An Integrated Approach. In: Journal of Construction Engineering and Management, v. 149, n. 11 (November 2023).

    https://doi.org/10.1061/jcemd4.coeng-13673

  3. Duan, Pinsheng / Zhou, Jianliang / Fan, Wenhan (2022): Safety tag generation and training material recommendation for construction workers: a persona-based approach. In: Engineering, Construction and Architectural Management, v. 31, n. 1 (September 2022).

    https://doi.org/10.1108/ecam-12-2021-1143

  4. Chen, Dawei / Zhou, Jianliang / Duan, Pinsheng / Zhang, Jiaqi (2023): Integrating knowledge management and BIM for safety risk identification of deep foundation pit construction. In: Engineering, Construction and Architectural Management, v. 30, n. 8 (Januar 2023).

    https://doi.org/10.1108/ecam-10-2021-0934

  5. Duan, Pinsheng / Zhou, Jianliang (2022): A science mapping approach-based review of near-miss research in construction. In: Engineering, Construction and Architectural Management, v. 30, n. 6 (August 2022).

    https://doi.org/10.1108/ecam-09-2021-0797

  6. Duan, Pinsheng / Zhou, Jianliang / Tao, Shiwei (2023): Risk events recognition using smartphone and machine learning in construction workers' material handling tasks. In: Engineering, Construction and Architectural Management, v. 30, n. 8 (Januar 2023).

    https://doi.org/10.1108/ecam-10-2021-0937

  7. Duan, Pinsheng / Zhou, Jianliang (2021): Cascading vulnerability analysis of unsafe behaviors of construction workers from the perspective of network modeling. In: Engineering, Construction and Architectural Management, v. 30, n. 3 (November 2021).

    https://doi.org/10.1108/ecam-06-2021-0475

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