A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications

O Avci, O Abdeljaber, S Kiranyaz, M Hussein… - Mechanical systems and …, 2021 - Elsevier
Monitoring structural damage is extremely important for sustaining and preserving the
service life of civil structures. While successful monitoring provides resolute and staunch …

Error metrics and performance fitness indicators for artificial intelligence and machine learning in engineering and sciences

MZ Naser, AH Alavi - Architecture, Structures and Construction, 2023 - Springer
Artificial intelligence (AI) and Machine learning (ML) train machines to achieve a high level
of cognition and perform human-like analysis. Both AI and ML seemingly fit into our daily …

Implementing ensemble learning methods to predict the shear strength of RC deep beams with/without web reinforcements

DC Feng, WJ Wang, S Mangalathu, G Hu, T Wu - Engineering Structures, 2021 - Elsevier
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 …

Emerging artificial intelligence methods in structural engineering

H Salehi, R Burgueño - Engineering structures, 2018 - Elsevier
Artificial intelligence (AI) is proving to be an efficient alternative approach to classical
modeling techniques. AI refers to the branch of computer science that develops machines …

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 …

Computational design optimization of concrete mixtures: A review

MA DeRousseau, JR Kasprzyk, WV Srubar Iii - Cement and Concrete …, 2018 - Elsevier
A comprehensive review of optimization research concerning the design and proportioning
of concrete mixtures is presented herein. Mixture design optimization is motivated by an ever …

Artificial neural network based modelling approach for strength prediction of concrete incorporating agricultural and construction wastes

MA Getahun, SM Shitote, ZCA Gariy - Construction and Building Materials, 2018 - Elsevier
Construction debris and agricultural wastes are among the major environmental concerns in
the world. Construction debris consumes about 28% of the nation's landfill facilities. Over …

Comparative analysis of various machine learning algorithms to predict strength properties of sustainable green concrete containing waste foundry sand

MF Javed, M Khan, M Fawad, H Alabduljabbar… - Scientific Reports, 2024 - nature.com
The use of waste foundry sand (WFS) in concrete production has gained attention as an eco-
friendly approach to waste reduction and enhancing cementitious materials. However …

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 …

Development of novel design strength model for sustainable concrete columns: A new machine learning-based approach

MJ Munir, SMS Kazmi, YF Wu, X Lin… - Journal of Cleaner …, 2022 - Elsevier
Billions of tons of construction and demolition (C&D) waste generation is causing global
environmental crises. The application of C&D waste in concrete columns is a sustainable …