State-of-the-art AI-based computational analysis in civil engineering
C Wang, L Song, Z Yuan, J Fan - Journal of Industrial Information …, 2023 - Elsevier
With the informatization of the building and infrastructure industry, conventional analysis
methods are gradually proving inadequate in meeting the demands of the new era, such as …
methods are gradually proving inadequate in meeting the demands of the new era, such as …
Hybrid machine learning model and Shapley additive explanations for compressive strength of sustainable concrete
Y Wu, Y Zhou - Construction and Building Materials, 2022 - Elsevier
The application of the traditional support vector regression (SVR) model to predict the
compressive strength of concrete faces the challenge of parameter tuning. To this end, a …
compressive strength of concrete faces the challenge of parameter tuning. To this end, a …
Artificial intelligence techniques in advanced concrete technology: A comprehensive survey on 10 years research trend
R Kazemi - Engineering Reports, 2023 - Wiley Online Library
Advanced concrete technology is the science of efficient, cost‐effective, and safe design in
civil engineering projects. Engineers and concrete designers are generally faced with the …
civil engineering projects. Engineers and concrete designers are generally faced with the …
Compressive strength prediction of lightweight concrete: Machine learning models
A Kumar, HC Arora, NR Kapoor, MA Mohammed… - Sustainability, 2022 - mdpi.com
Concrete is the most commonly used construction material. The physical properties of
concrete vary with the type of concrete, such as high and ultra-high-strength concrete, fibre …
concrete vary with the type of concrete, such as high and ultra-high-strength concrete, fibre …
[HTML][HTML] Interpretable machine learning-based analysis of hydration and carbonation of carbonated reactive magnesia cement mixes
Y Peng, C Unluer - Journal of Cleaner Production, 2024 - Elsevier
This study explored the influence of different input variables on the hydration and
carbonation degree of carbonated reactive magnesia cement (RMC) system by employing …
carbonation degree of carbonated reactive magnesia cement (RMC) system by employing …
Buckling and ultimate load prediction models for perforated steel beams using machine learning algorithms
VV Degtyarev, KD Tsavdaridis - Journal of Building Engineering, 2022 - Elsevier
Large web openings introduce complex structural behaviors and additional failure modes of
steel cellular beams, which must be considered in the design using laborious calculations …
steel cellular beams, which must be considered in the design using laborious calculations …
[HTML][HTML] ANN-based rapid seismic fragility analysis for multi-span concrete bridges
Rapid seismic fragility analysis of regular bridges is necessary for the increasingly utilized
regional seismic risk assessment, which is usually difficult using numerical methods owing …
regional seismic risk assessment, which is usually difficult using numerical methods owing …
Physics-supervised ensemble learning model for predicting failure modes of reinforced concrete columns
In order to overcome the limitation that traditional prediction models lack of learning ability of
physical laws and with low generalization performance, a novel physics-supervised …
physical laws and with low generalization performance, a novel physics-supervised …
Comprehensive functional resilience assessment methodology for bridge networks using data-driven fragility models
This paper proposes a probabilistic seismic resilience assessment methodology for bridge
networks subjected to spatially correlated earthquakes. The proposed method integrates the …
networks subjected to spatially correlated earthquakes. The proposed method integrates the …
Integrated method for intelligent structural design of steel frames based on optimization and machine learning algorithm
W Shan, J Liu, J Zhou - Engineering Structures, 2023 - Elsevier
Optimization methods using metaheuristic algorithms have been widely used in steel frame
design to improve the inefficient traditional design method due to repeated model tuning and …
design to improve the inefficient traditional design method due to repeated model tuning and …