Xingquan Guan 
- (2023): An adapted LSTM-DRRNet approach for predicting floor acceleration response spectrum. In: Engineering Structures, v. 295 (November 2023).
- (2023): Collaborative filtering‐based collapse fragility assessment. In: Earthquake Engineering and Structural Dynamics, v. 52, n. 11 (June 2023).
- (2023): A multi-source data-driven approach for evaluating the seismic response of non-ductile reinforced concrete moment frames. In: Engineering Structures, v. 278 (March 2023).
- (2022): Bias-variance tradeoff in machine learning: Theoretical formulation and implications to structural engineering applications. In: Structures, v. 46 (December 2022).
- (2022): Accurate prediction of concrete compressive strength based on explainable features using deep learning. In: Construction and Building Materials, v. 329 (April 2022).
- (2021): Fire resistance behavior of T-stub joint components under transient heat transfer conditions. In: Engineering Structures, v. 237 (June 2021).
- (2021): Seismic Drift Demand Estimation for Steel Moment Frame Buildings: From Mechanics-Based to Data-Driven Models. In: Journal of Structural Engineering (ASCE), v. 147, n. 6 (June 2021).
- (2020): Python-based computational platform to automate seismic design, nonlinear structural model construction and analysis of steel moment resisting frames. In: Engineering Structures, v. 224 (December 2020).
- (2018): Seismic performance of a self-centering steel moment frame building: From component-level modeling to economic loss assessment. In: Journal of Constructional Steel Research, v. 150 (November 2018).
- (2019): Dynamic behavior of CHS-SHS tubular T-joints subjected to low-velocity impact loading. In: Engineering Structures, v. 183 (March 2019).
- (2018): Fire-Resistance Behavior of Completely Overlapped Tubular Joints under Lap Brace Axial Loading. In: Journal of Structural Engineering (ASCE), v. 144, n. 9 (September 2018).
Structurae cooperates with
