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 in concrete science: applications, challenges, and best practices
Concrete, as the most widely used construction material, is inextricably connected with
human development. Despite conceptual and methodological progress in concrete science …
human development. Despite conceptual and methodological progress in concrete science …
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 …
Prediction of chloride diffusivity in concrete using artificial neural network: Modelling and performance evaluation
Chloride ingression is the main reason for causing durability degradation of reinforced
concrete (RC) structures. In this study, the distinguishing features of artificial neural network …
concrete (RC) structures. In this study, the distinguishing features of artificial neural network …
Prediction of cement-based mortars compressive strength using machine learning techniques
The application of artificial neural networks in mapping the mechanical characteristics of the
cement-based materials is underlined in previous investigations. However, this machine …
cement-based materials is underlined in previous investigations. However, this machine …
Applications of gene expression programming and regression techniques for estimating compressive strength of bagasse ash based concrete
Compressive strength is one of the important property of concrete and depends on many
factors. Most of the concrete compressive strength predictive models mainly rely on …
factors. Most of the concrete compressive strength predictive models mainly rely on …
Supervised deep restricted Boltzmann machine for estimation of concrete
Costly and time-consuming destructive methods are usually used to determine the
properties of alternative concrete mixtures. To reduce cost and time, statistical and neural …
properties of alternative concrete mixtures. To reduce cost and time, statistical and neural …
[HTML][HTML] Predicting ultra-high-performance concrete compressive strength using gene expression programming method
There have been extensive experimental studies available on the composition and
characteristics of Ultra-High-Performance concrete (UHPC). However, the relation between …
characteristics of Ultra-High-Performance concrete (UHPC). However, the relation between …
Prediction of compressive strength of recycled aggregate concrete using artificial neural networks
Recycled aggregates are substantially different in composition and properties compared
with natural aggregates, leading it hard to predict the performance of recycled aggregate …
with natural aggregates, leading it hard to predict the performance of recycled aggregate …
Multi-target regression via input space expansion: treating targets as inputs
In many practical applications of supervised learning the task involves the prediction of
multiple target variables from a common set of input variables. When the prediction targets …
multiple target variables from a common set of input variables. When the prediction targets …