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

  1. Yuan, Dongyang / Gu, Chongshi / Qin, Xiangnan / Shao, Chenfei / He, Jing (2022): Performance-improved TSVR-based DHM model of super high arch dams using measured air temperature. In: Engineering Structures, v. 250 (Januar 2022).

    https://doi.org/10.1016/j.engstruct.2021.113400

  2. Wang, Shaowei / Xu, Yingli / Gu, Chongshi / Xia, Qun / Hu, Kun (2019): Two spatial association–considered mathematical models for diagnosing the long-term balanced relationship and short-term fluctuation of the deformation behaviour of high concrete arch dams. In: Structural Health Monitoring, v. 19, n. 5 (Oktober 2019).

    https://doi.org/10.1177/1475921719884861

  3. Gu, Chongshi / Cao, Xin / Xu, Bo (2019): Stochastic Inversion Method for Concrete Dams on the Basis of Bayesian Back Analysis Theory. In: Advances in Civil Engineering, v. 2019 ( 2019).

    https://doi.org/10.1155/2019/5943913

  4. Chen, Bo / Fu, Xiao / Guo, Xuyuan / Gu, Chongshi / Shao, Chenfei / Qin, Xiangnan (2019): Zoning Elastic Modulus Inversion for High Arch Dams Based on the PSOGSA-SVM Method. In: Advances in Civil Engineering, v. 2019 ( 2019).

    https://doi.org/10.1155/2019/7936513

  5. Li, Hui / Bao, Tengfei / Gu, Chongshi / Chen, Bo (2019): Vibration feature extraction based on the improved variational mode decomposition and singular spectrum analysis combination algorithm. In: Advances in Structural Engineering, v. 22, n. 4 (Februar 2019).

    https://doi.org/10.1177/1369433218818921

  6. Dai, Bo / Gu, Chongshi / Zhao, Erfeng / Qin, Xiangnan (2018): Statistical model optimized random forest regression model for concrete dam deformation monitoring. In: Structural Control and Health Monitoring, v. 25, n. 6 (Juni 2018).

    https://doi.org/10.1002/stc.2170

  7. Liu, Hezhi / Zhang, Qian / Gu, Chongshi / Su, Huaizhi / Li, Victor (2017): Self-healing of microcracks in Engineered Cementitious Composites under sulfate and chloride environment. In: Construction and Building Materials, v. 153 (Oktober 2017).

    https://doi.org/10.1016/j.conbuildmat.2017.07.126

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