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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. Cui, Jiaming / Xing, Guohua / Miao, Pengyong / Zhang, Yifan / Chang, Zhaoqun / Khan, Arslan Qayyum (2024): Flexural behavior of RC beams strengthened with BFRP bars and CFRP U-jackets: Experimental and numerical analysis. In: Journal of Building Engineering, v. 97 (November 2024).

    https://doi.org/10.1016/j.jobe.2024.110932

  2. Miao, Pengyong / Srimahachota, Teeranai / Wu, Yanru / Ma, Shengchi / Zhou, Chunjuan (2024): Information fusion-based maintenance strategies selection for coastal concrete bridges using recycled fishing nets. In: Structures, v. 63 (May 2024).

    https://doi.org/10.1016/j.istruc.2024.106456

  3. Qiao, Lei / Miao, Pengyong / Xing, Guohua / Luo, Xiaobao / Ma, Jun / Farooq, Muhammad Aboubakar (2023): Interpretable machine learning model for predicting freeze-thaw damage of dune sand and fiber reinforced concrete. In: Case Studies in Construction Materials, v. 19 (December 2023).

    https://doi.org/10.1016/j.cscm.2023.e02453

  4. Xing, Guohua / Luo, Xiaobao / Miao, Pengyong / Qiao, Lei / Yu, Xiaoguang / Qin, Yongjun (2023): Proposed Mix Design Method for Dune Sand Concrete Using Close Packing Model and Mortar Film Thickness Theory. In: Journal of Materials in Civil Engineering (ASCE), v. 35, n. 11 (November 2023).

    https://doi.org/10.1061/jmcee7.mteng-16142

  5. Xing, Guohua / Xu, Yangchen / Huang, Jiao / Lu, Yongjian / Miao, Pengyong / Chindasiriphan, Pattharaphon / Jongvivatsakul, Pitcha / Ma, Kaize (2023): Research on the mechanical properties of steel fibers reinforced carbon nanotubes concrete. In: Construction and Building Materials, v. 392 (August 2023).

    https://doi.org/10.1016/j.conbuildmat.2023.131880

  6. Miao, Pengyong / Xing, Guohua / Ma, Shengchi / Srimahachota, Teeranai (2023): Deep Learning–Based Inspection Data Mining and Derived Information Fusion for Enhanced Bridge Deterioration Assessment. In: Journal of Bridge Engineering (ASCE), v. 28, n. 8 (August 2023).

    https://doi.org/10.1061/jbenf2.beeng-6053

  7. Luo, Xiaobao / Xing, Guohua / Qiao, Lei / Miao, Pengyong / Yu, Xiaoguang / Ma, Kaize (2023): Multi-objective optimization of the mix proportion for dune sand concrete based on response surface methodology. In: Construction and Building Materials, v. 366 (February 2023).

    https://doi.org/10.1016/j.conbuildmat.2022.129928

  8. Miao, Pengyong / Yokota, Hiroshi (2024): Comparison of Markov chain and recurrent neural network in predicting bridge deterioration considering various factors. In: Structure and Infrastructure Engineering, v. 20, n. 2 (June 2024).

    https://doi.org/10.1080/15732479.2022.2087691

  9. Miao, Pengyong / Srimahachota, Teeranai (2021): Cost-effective system for detection and quantification of concrete surface cracks by combination of convolutional neural network and image processing techniques. In: Construction and Building Materials, v. 293 (July 2021).

    https://doi.org/10.1016/j.conbuildmat.2021.123549

  10. Miao, Pengyong / Yokota, Hiroshi / Zhang, Yafen (2023): Deterioration prediction of existing concrete bridges using a LSTM recurrent neural network. In: Structure and Infrastructure Engineering, v. 19, n. 4 (July 2023).

    https://doi.org/10.1080/15732479.2021.1951778

  11. Miao, Pengyong (2021): Prediction-Based Maintenance of Existing Bridges Using Neural Network and Sensitivity Analysis. In: Advances in Civil Engineering, v. 2021 (January 2021).

    https://doi.org/10.1155/2021/4598337

  12. Miao, Pengyong / Yokota, Hiroshi / Zhang, Yafen (2022): Extracting procedures of key data from a structural maintenance database. In: Structure and Infrastructure Engineering, v. 18, n. 2 (June 2022).

    https://doi.org/10.1080/15732479.2020.1838561

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