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Probabilistic Machine-Learning Methods for Performance Prediction of Structure and Infrastructures through Natural Gradient Boosting
Publisher: ASCE
Abstract: The capabilities of data-driven models based on machine learning (ML) algorithms in offering accurate predictions of structural responses efficiently have been demonstrated in numerous recent studies. However, efforts to ...
Interpretable XGBoost-SHAP Machine-Learning Model for Shear Strength Prediction of Squat RC Walls
Publisher: ASCE
Abstract: RC shear walls are commonly used as lateral load-resisting elements in seismic regions, and the estimation of their shear strengths can become simultaneously design-critical and complex when they have so-called squat ...
Effectiveness Assessment of TMDs in Bridges under Strong Winds Incorporating Machine-Learning Techniques
Publisher: ASCE
Abstract: Tuned mass dampers (TMDs) are widely used to control excessive wind-induced vibration in the box girders of long-span bridges. Although the optimal design of TMDs has been investigated abundantly in the last few years, the ...