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 …
Predictive models for concrete properties using machine learning and deep learning approaches: A review
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 …
Its global production rate is increasing to meet demand. Mechanical properties of concrete …
Predictive modeling for sustainable high-performance concrete from industrial wastes: A comparison and optimization of models using ensemble learners
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 …
ambiguity exists with its mix design. Compressive strength can vary with the composition …
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 …
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 …
for predicting the compressive strength of concrete. This approach employs the adaptive …
Predicting the compressive strength of normal and High-Performance Concretes using ANN and ANFIS hybridized with Grey Wolf Optimizer
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 …
save in time, energy, and cost and also provide information about scheduling for …
Machine learning techniques for structural health monitoring of heritage buildings: A state-of-the-art review and case studies
M Mishra - Journal of Cultural Heritage, 2021 - Elsevier
This paper performed a systematic review of the various machine learning (ML) techniques
applied to assess the health condition of heritage buildings. More robust predictive models …
applied to assess the health condition of heritage buildings. More robust predictive models …
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 …
Predictive modeling of mechanical properties of silica fume-based green concrete using artificial intelligence approaches: MLPNN, ANFIS, and GEP
Silica fume (SF) is a mineral additive that is widely used in the construction industry when
producing sustainable concrete. The integration of SF in concrete as a partial replacement …
producing sustainable concrete. The integration of SF in concrete as a partial replacement …
Predictive modelling for the acid resistance of cement-based composites modified with eggshell and glass waste for sustainable and resilient building materials
The increasing demand for cement-based composites (CBCs) due to the advancement of
infrastructure causes the exhaustion of natural materials and environmental pollution. Also …
infrastructure causes the exhaustion of natural materials and environmental pollution. Also …