Predictive models for concrete properties using machine learning and deep learning approaches: A review

MM Moein, A Saradar, K Rahmati… - Journal of Building …, 2023 - Elsevier
Concrete is one of the most widely used materials in various civil engineering applications.
Its global production rate is increasing to meet demand. Mechanical properties of concrete …

[HTML][HTML] 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 …

[HTML][HTML] A novel approach to explain the black-box nature of machine learning in compressive strength predictions of concrete using Shapley additive explanations …

IU Ekanayake, DPP Meddage, U Rathnayake - Case Studies in …, 2022 - Elsevier
Abstract Machine learning (ML) techniques are often employed for the accurate prediction of
the compressive strength of concrete. Despite higher accuracy, previous ML models failed to …

Predictive modeling for sustainable high-performance concrete from industrial wastes: A comparison and optimization of models using ensemble learners

F Farooq, W Ahmed, A Akbar, F Aslam… - Journal of Cleaner …, 2021 - Elsevier
The cementitious matrix of high-performance concrete (HPC) is highly complex, and
ambiguity exists with its mix design. Compressive strength can vary with the composition …

Machine learning prediction of mechanical properties of concrete: Critical review

WB Chaabene, M Flah, ML Nehdi - Construction and Building Materials, 2020 - Elsevier
Accurate prediction of the mechanical properties of concrete has been a concern since
these properties are often required by design codes. The emergence of new concrete …

Machine learning-based compressive strength prediction for concrete: An adaptive boosting approach

DC Feng, ZT Liu, XD Wang, Y Chen, JQ Chang… - … and Building Materials, 2020 - Elsevier
In this paper, an intelligent approach based on the machine learning technique is proposed
for predicting the compressive strength of concrete. This approach employs the adaptive …

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 …

[HTML][HTML] Estimating compressive strength of concrete using neural electromagnetic field optimization

MR Akbarzadeh, H Ghafourian, A Anvari… - Materials, 2023 - mdpi.com
Concrete compressive strength (CCS) is among the most important mechanical
characteristics of this widely used material. This study develops a novel integrative method …

Compressive strength prediction of environmentally friendly concrete using artificial neural networks

H Naderpour, AH Rafiean, P Fakharian - Journal of building engineering, 2018 - Elsevier
Solid waste in the form of construction debris is one of the major environmental concerns in
the world. Over 20 million tons of construction waste materials are generated in Tehran each …