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 …
intelligence (AI). It provides a unique opportunity to make structural engineering more …
Roles of artificial intelligence in construction engineering and management: A critical review and future trends
With the extensive adoption of artificial intelligence (AI), construction engineering and
management (CEM) is experiencing a rapid digital transformation. Since AI-based solutions …
management (CEM) is experiencing a rapid digital transformation. Since AI-based solutions …
[HTML][HTML] Deep learning in the construction industry: A review of present status and future innovations
The construction industry is known to be overwhelmed with resource planning, risk
management and logistic challenges which often result in design defects, project delivery …
management and logistic challenges which often result in design defects, project delivery …
Artificial intelligence, machine learning, and deep learning in structural engineering: a scientometrics review of trends and best practices
Artificial Intelligence (AI), machine learning (ML), and deep learning (DL) are emerging
techniques capable of delivering elegant and affordable solutions which can surpass those …
techniques capable of delivering elegant and affordable solutions which can surpass those …
Efficient machine learning models for prediction of concrete strengths
In this study, an efficient implementation of machine learning models to predict compressive
and tensile strengths of high-performance concrete (HPC) is presented. Four predictive …
and tensile strengths of high-performance concrete (HPC) is presented. Four predictive …
Machine learning-based prediction for compressive and flexural strengths of steel fiber-reinforced concrete
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 …
concrete because of the addition of discontinuous fibers. The development of strengths …
[HTML][HTML] Deep learning for topology optimization of 2D metamaterials
HT Kollmann, DW Abueidda, S Koric, E Guleryuz… - Materials & Design, 2020 - Elsevier
Data-driven models are rising as an auspicious method for the geometrical design of
materials and structural systems. Nevertheless, existing data-driven models customarily …
materials and structural systems. Nevertheless, existing data-driven models customarily …
Strategic progress in foam stabilisation towards high-performance foam concrete for building sustainability: A state-of-the-art review
Lightweight, high energy reservation and excellent functional performance are the main
benefits of cellular concrete. Its properties mainly depends on the pore characteristics …
benefits of cellular concrete. Its properties mainly depends on the pore characteristics …
Estimating compressive strength of concrete using neural electromagnetic field optimization
Concrete compressive strength (CCS) is among the most important mechanical
characteristics of this widely used material. This study develops a novel integrative method …
characteristics of this widely used material. This study develops a novel integrative method …
Predictive modeling of compressive strength of sustainable rice husk ash concrete: Ensemble learner optimization and comparison
One of the largest sources of greenhouse gas (GHG) emissions is the construction concrete
industry which has alone 50% of the world's emissions. One possible remedy to mitigate the …
industry which has alone 50% of the world's emissions. One possible remedy to mitigate the …