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 …
Machine learning prediction of mechanical properties of concrete: Critical review
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 …
these properties are often required by design codes. The emergence of new concrete …
A generalized method to predict the compressive strength of high-performance concrete by improved random forest algorithm
Q Han, C Gui, J Xu, G Lacidogna - Construction and Building Materials, 2019 - Elsevier
The prediction results of high-performance concrete compressive strength (HPCCS) based
on machine learning methods are seriously influenced by input variables and model …
on machine learning methods are seriously influenced by input variables and model …
Linear and non-linear SVM prediction for fresh properties and compressive strength of high volume fly ash self-compacting concrete
M Azimi-Pour, H Eskandari-Naddaf… - Construction and Building …, 2020 - Elsevier
Support vector machines (SVMs) have recently been used to model the properties of low
volume fly ash self-compacting concrete (LVF-SCC) by means of kernel functions to …
volume fly ash self-compacting concrete (LVF-SCC) by means of kernel functions to …
Metaheuristic optimization of Levenberg–Marquardt-based artificial neural network using particle swarm optimization for prediction of foamed concrete compressive …
Foamed concrete (FC) shows advantageous applications in civil engineering, such as
reduction in dead loads, contribution to energy conservation, or decrease the construction …
reduction in dead loads, contribution to energy conservation, or decrease the construction …
Compressive strength of Foamed Cellular Lightweight Concrete simulation: New development of hybrid artificial intelligence model
Accurate prediction of compressive strength (fc) is one of the crucial problems in the
concrete industry. In this study, novel self-adaptive and formula-based model called …
concrete industry. In this study, novel self-adaptive and formula-based model called …
Deep learning-based investigation of wind pressures on tall building under interference effects
Interference effects of tall buildings have attracted numerous studies due to the boom of
clusters of buildings in megacities. To fully understand the interference effects, it often …
clusters of buildings in megacities. To fully understand the interference effects, it often …
[PDF][PDF] Prediction of the compressive strength of self-compacting concrete using surrogate models
In this paper, surrogate models such as multivariate adaptive regression splines (MARS)
and M5P model tree (M5P MT) methods have been investigated in order to propose a new …
and M5P model tree (M5P MT) methods have been investigated in order to propose a new …
Towards sustainable construction: Machine learning based predictive models for strength and durability characteristics of blended cement concrete
Supplementary cementitious materials (SCMs) are widely utilized in concrete mixtures,
either substituting a part of the cement content or replacing a portion of clinker in cement …
either substituting a part of the cement content or replacing a portion of clinker in cement …
[HTML][HTML] An explainable machine learning model to predict and elucidate the compressive behavior of high-performance concrete
Abstract Machine Learning (ML) has made significant progress in several fields, and
materials science is no exception. ML models are popular in the materials science …
materials science is no exception. ML models are popular in the materials science …