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 …

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 …

Artificial intelligence, machine learning, and deep learning in structural engineering: a scientometrics review of trends and best practices

ATG Tapeh, MZ Naser - Archives of Computational Methods in …, 2023 - Springer
Artificial Intelligence (AI), machine learning (ML), and deep learning (DL) are emerging
techniques capable of delivering elegant and affordable solutions which can surpass those …

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 …

[HTML][HTML] Predicting the compressive strength of concrete with fly ash admixture using machine learning algorithms

H Song, A Ahmad, F Farooq, KA Ostrowski… - … and Building Materials, 2021 - Elsevier
The cementitious composites have different properties in the changing environment. Thus,
knowing their mechanical properties is very important for safety reasons. The most important …

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 …

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 …

A novel hybrid extreme learning machine–grey wolf optimizer (ELM-GWO) model to predict compressive strength of concrete with partial replacements for cement

M Shariati, MS Mafipour, B Ghahremani… - Engineering with …, 2022 - Springer
Compressive strength of concrete is one of the most determinant parameters in the design of
engineering structures. This parameter is generally determined by conducting several tests …

Short-term water quality variable prediction using a hybrid CNN–LSTM deep learning model

R Barzegar, MT Aalami, J Adamowski - … Environmental Research and Risk …, 2020 - Springer
Water quality monitoring is an important component of water resources management. In
order to predict two water quality variables, namely dissolved oxygen (DO; mg/L) and …

Emerging materials intelligence ecosystems propelled by machine learning

R Batra, L Song, R Ramprasad - Nature Reviews Materials, 2021 - nature.com
The age of cognitive computing and artificial intelligence (AI) is just dawning. Inspired by its
successes and promises, several AI ecosystems are blossoming, many of them within the …