Pengyong Miao 
- (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).
- (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).
- (2023): Research on the mechanical properties of steel fibers reinforced carbon nanotubes concrete. In: Construction and Building Materials, v. 392 (August 2023).
- (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).
- (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).
- (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).
- (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).
- (2023): Deterioration prediction of existing concrete bridges using a LSTM recurrent neural network. In: Structure and Infrastructure Engineering, v. 19, n. 4 (July 2023).
- (2021): Prediction-Based Maintenance of Existing Bridges Using Neural Network and Sensitivity Analysis. In: Advances in Civil Engineering, v. 2021 (January 2021).
- (2022): Extracting procedures of key data from a structural maintenance database. In: Structure and Infrastructure Engineering, v. 18, n. 2 (June 2022).
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