[HTML][HTML] Artificial intelligence and smart vision for building and construction 4.0: Machine and deep learning methods and applications

SK Baduge, S Thilakarathna, JS Perera… - Automation in …, 2022 - Elsevier
This article presents a state-of-the-art review of the applications of Artificial Intelligence (AI),
Machine Learning (ML), and Deep Learning (DL) in building and construction industry 4.0 in …

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 …

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 …

Machine learning and deep learning in energy systems: A review

MM Forootan, I Larki, R Zahedi, A Ahmadi - Sustainability, 2022 - mdpi.com
With population increases and a vital need for energy, energy systems play an important
and decisive role in all of the sectors of society. To accelerate the process and improve the …

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 …

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 …

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 …

Machine learning-based prediction for compressive and flexural strengths of steel fiber-reinforced concrete

MC Kang, DY Yoo, R Gupta - Construction and Building Materials, 2021 - Elsevier
Steel fiber-reinforced concrete (SFRC) has a performance superior to that of normal
concrete because of the addition of discontinuous fibers. The development of strengths …