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 …

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 …

Predicting concrete compressive strength using hybrid ensembling of surrogate machine learning models

PG Asteris, AD Skentou, A Bardhan, P Samui… - Cement and Concrete …, 2021 - Elsevier
This study aims to implement a hybrid ensemble surrogate machine learning technique in
predicting the compressive strength (CS) of concrete, an important parameter used for …

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 …

A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength

DJ Armaghani, PG Asteris - Neural Computing and Applications, 2021 - Springer
Despite the extensive use of mortars materials in constructions over the last decades, there
is not yet a reliable and robust method, available in the literature, which can estimate its …

Predicting the compressive strength of normal and High-Performance Concretes using ANN and ANFIS hybridized with Grey Wolf Optimizer

EM Golafshani, A Behnood, M Arashpour - Construction and Building …, 2020 - Elsevier
Achieving a reliable model for predicting the compressive strength (CS) of concrete can
save in time, energy, and cost and also provide information about scheduling for …

Predicting the compressive strength of concrete containing metakaolin with different properties using ANN

MJ Moradi, M Khaleghi, J Salimi, V Farhangi… - Measurement, 2021 - Elsevier
The advantages of using Metakaolin (MK) as a supplementary cementitious material have
led this highly active pozzolan to be widely used in the concrete industry. Awareness of the …

Prediction of cement-based mortars compressive strength using machine learning techniques

PG Asteris, M Koopialipoor, DJ Armaghani… - Neural Computing and …, 2021 - Springer
The application of artificial neural networks in mapping the mechanical characteristics of the
cement-based materials is underlined in previous investigations. However, this machine …

Mapping and holistic design of natural hydraulic lime mortars

M Apostolopoulou, PG Asteris, DJ Armaghani… - Cement and concrete …, 2020 - Elsevier
In recent years, the study of high hydraulicity natural hydraulic lime (NHL5) mortars has
been in the focus of many researchers, as it is considered a compatible, eco-friendly binding …

Artificial intelligence approaches for prediction of compressive strength of geopolymer concrete

DV Dao, HB Ly, SH Trinh, TT Le, BT Pham - Materials, 2019 - mdpi.com
Geopolymer concrete (GPC) has been used as a partial replacement of Portland cement
concrete (PCC) in various construction applications. In this paper, two artificial intelligence …