Machine learning for structural engineering: A state-of-the-art review
HT Thai - Structures, 2022 - Elsevier
Abstract Machine learning (ML) has become the most successful branch of artificial
intelligence (AI). It provides a unique opportunity to make structural engineering more …
intelligence (AI). It provides a unique opportunity to make structural engineering more …
The promise of implementing machine learning in earthquake engineering: A state-of-the-art review
Machine learning (ML) has evolved rapidly over recent years with the promise to
substantially alter and enhance the role of data science in a variety of disciplines. Compared …
substantially alter and enhance the role of data science in a variety of disciplines. Compared …
Interpretable XGBoost-SHAP machine-learning model for shear strength prediction of squat RC walls
DC Feng, WJ Wang, S Mangalathu… - Journal of Structural …, 2021 - ascelibrary.org
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 …
and the estimation of their shear strengths can become simultaneously design-critical and …
Failure mode and effects analysis of RC members based on machine-learning-based SHapley Additive exPlanations (SHAP) approach
Abstract Machine learning approaches can establish the complex and non-linear
relationship among input and response variables for the seismic damage assessment of …
relationship among input and response variables for the seismic damage assessment of …
Data-driven shear strength prediction of steel fiber reinforced concrete beams using machine learning approach
The incorporation of steel fibers in a concrete mix enhances the shear capacity of reinforced
concrete beams and a comprehensive understanding of this phenomenon is imperative to …
concrete beams and a comprehensive understanding of this phenomenon is imperative to …
Implementing ensemble learning methods to predict the shear strength of RC deep beams with/without web reinforcements
This paper presents a practical yet comprehensive implementation of the ensemble methods
for prediction of the shear strength for reinforced concrete deep beams with/without web …
for prediction of the shear strength for reinforced concrete deep beams with/without web …
Machine learning for risk and resilience assessment in structural engineering: Progress and future trends
Population growth, economic development, and rapid urbanization in many areas have led
to increased exposure and vulnerability of structural and infrastructure systems to hazards …
to increased exposure and vulnerability of structural and infrastructure systems to hazards …
Explainable machine learning models for predicting the axial compression capacity of concrete filled steel tubular columns
Concrete-filled steel tubular (CFST) columns have been popular in the construction industry
due to enhanced mechanical properties such as higher strength and ductility, higher seismic …
due to enhanced mechanical properties such as higher strength and ductility, higher seismic …
Data-driven machine-learning-based seismic failure mode identification of reinforced concrete shear walls
A reinforced concrete shear wall is one of the most critical structural members in buildings, in
terms of carrying lateral loads. Despite its importance, post-earthquake reconnaissance and …
terms of carrying lateral loads. Despite its importance, post-earthquake reconnaissance and …
Failure mode classification and bearing capacity prediction for reinforced concrete columns based on ensemble machine learning algorithm
DC Feng, ZT Liu, XD Wang, ZM Jiang… - Advanced Engineering …, 2020 - Elsevier
Failure mode (FM) and bearing capacity of reinforced concrete (RC) columns are key
concerns in structural design and/or performance assessment procedures. The failure types …
concerns in structural design and/or performance assessment procedures. The failure types …