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 …
Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights
Conventional damage detection techniques are gradually being replaced by state-of-the-art
smart monitoring and decision-making solutions. Near real-time and online damage …
smart monitoring and decision-making solutions. Near real-time and online damage …
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 …
Applications of artificial intelligence for disaster management
Natural hazards have the potential to cause catastrophic damage and significant
socioeconomic loss. The actual damage and loss observed in the recent decades has …
socioeconomic loss. The actual damage and loss observed in the recent decades has …
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 …
[HTML][HTML] Explainable machine learning model and reliability analysis for flexural capacity prediction of RC beams strengthened in flexure with FRCM
This paper presents a data-driven approach to determine the load and flexural capacities of
reinforced concrete (RC) beams strengthened with fabric reinforced cementitious matrix …
reinforced concrete (RC) beams strengthened with fabric reinforced cementitious matrix …
An engineer's guide to eXplainable Artificial Intelligence and Interpretable Machine Learning: Navigating causality, forced goodness, and the false perception of …
MZ Naser - Automation in Construction, 2021 - Elsevier
While artificial intelligence (AI), and by extension machine learning (ML), continues to be
adopted in parallel engineering disciplines, the integration of AI/ML into the structural …
adopted in parallel engineering disciplines, the integration of AI/ML into the structural …
Data‐driven rapid damage evaluation for life‐cycle seismic assessment of regional reinforced concrete bridges
Rapid and accurate post‐earthquake damage evaluation of regional reinforced concrete
(RC) bridges is a key issue for assessing the seismic resilience of cities and communities …
(RC) bridges is a key issue for assessing the seismic resilience of cities and communities …
Compressive strength prediction of hollow concrete masonry blocks using artificial intelligence algorithms
In this study, artificial intelligence algorithms are proposed for estimating the compressive
strength of hollow concrete block masonry prisms, including neural networks (ANN) …
strength of hollow concrete block masonry prisms, including neural networks (ANN) …
Machine-learning based vulnerability analysis of existing buildings
The paper presents a machine-learning based framework, named VULMA (VULnerability
analysis using MAchine-learning), for vulnerability analysis of existing buildings. The …
analysis using MAchine-learning), for vulnerability analysis of existing buildings. The …