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 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 …
[HTML][HTML] Predicting the compressive strength of concrete with fly ash admixture using machine learning algorithms
The cementitious composites have different properties in the changing environment. Thus,
knowing their mechanical properties is very important for safety reasons. The most important …
knowing their mechanical properties is very important for safety reasons. The most important …
[HTML][HTML] Compressive strength prediction of fly ash-based geopolymer concrete via advanced machine learning techniques
Concrete is a widely used construction material, and cement is its main constituent.
Production and utilization of cement severely affect the environment due to the emission of …
Production and utilization of cement severely affect the environment due to the emission of …
Prediction model for rice husk ash concrete using AI approach: Boosting and bagging algorithms
The use of rice husk ash (RHA) in concrete serves a positive role. The compressive strength
of RHA in concrete is predicted using supervised machine learning approaches such as …
of RHA in concrete is predicted using supervised machine learning approaches such as …
A comparative study of random forest and genetic engineering programming for the prediction of compressive strength of high strength concrete (HSC)
Supervised machine learning and its algorithm is an emerging trend for the prediction of
mechanical properties of concrete. This study uses an ensemble random forest (RF) and …
mechanical properties of concrete. This study uses an ensemble random forest (RF) and …
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 …
Comparative study of supervised machine learning algorithms for predicting the compressive strength of concrete at high temperature
High temperature severely affects the nature of the ingredients used to produce concrete,
which in turn reduces the strength properties of the concrete. It is a difficult and time …
which in turn reduces the strength properties of the concrete. It is a difficult and time …
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 …
Prediction of geopolymer concrete compressive strength using novel machine learning algorithms
The innovation of geopolymer concrete (GPC) plays a vital role not only in reducing the
environmental threat but also as an exceptional material for sustainable development. The …
environmental threat but also as an exceptional material for sustainable development. The …