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 …

Artificial intelligence techniques in advanced concrete technology: A comprehensive survey on 10 years research trend

R Kazemi - Engineering Reports, 2023‏ - Wiley Online Library
Advanced concrete technology is the science of efficient, cost‐effective, and safe design in
civil engineering projects. Engineers and concrete designers are generally faced with the …

Prediction of compressive strength of concrete modified with fly ash: Applications of neuro-swarm and neuro-imperialism models

A Mohammed, R Kurda, DJ Armaghani… - Computers and …, 2021‏ - koreascience.kr
In this study, two powerful techniques, namely particle swarm optimization (PSO) and
imperialist competitive algorithm (ICA) were selected and combined with a pre-developed …

Revealing the nonlinear behavior of steel flush endplate connections using ANN-based hybrid models

VL Tran, JK Kim - Journal of Building Engineering, 2022‏ - Elsevier
Connections are crucial zones in steel buildings since they provide interaction between
principal structural components (ie, beams, columns) and provide stability to the entire …

Artificial neural network calculations for a receding contact problem

EU Yaylacı, M Yaylacı, H Ölmez, A Birinci - Computers and Concrete, An …, 2020‏ - dbpia.co.kr
This paper investigates the artificial neural network (ANN) to predict the dimensionless
parameters for the maximum contact pressures and contact areas of a contact problem …

[PDF][PDF] Machine learning and RSM models for prediction of compressive strength of smart bio-concrete

HA Algaifi, SA Bakar, R Alyousef, ARM Sam… - Smart Struct …, 2021‏ - researchgate.net
In recent years, bacteria-based self-healing concrete has been widely exploited to improve
the compressive strength of concrete using different bacterial species. However, both the …

Evaluation of artificial neural network predicted mechanical properties of jute and bamboo fiber reinforced concrete along with silica fume

J Sridhar, R Gobinath, MS Kırgız - Journal of Natural Fibers, 2023‏ - Taylor & Francis
The aim of the effort is to estimate the effect of jute and bamboo fibers with silica fume (SF) of
different proportions on mechanical properties of concrete. Cube, cylinder and prism …

Machine Learning Models for Predicting Bond Strength of Deformed Bars in Concrete.

VV Degtyarev - ACI Structural Journal, 2022‏ - search.ebscohost.com
This paper proposes eight machine learning models for predicting the bond strength
between straight deformed reinforcing bars and concrete under tensile load. The models …

Predicting bond strength of corroded reinforcement by deep learning

H Tanyildizi - Computers and Concrete, 2022‏ - koreascience.kr
In this study, the extreme learning machine and deep learning models were devised to
estimate the bond strength of corroded reinforcement in concrete. The six inputs and one …

Artificial intelligence for the compressive strength prediction of novel ductile geopolymer composites

KK Yaswanth, J Revathy… - Computers and Concrete, 2021‏ - koreascience.kr
Abstract Engineered Geopolymer Composites has proved to be an excellent eco-friendly
strain hardening composite materials, as well as, it exhibits high tensile strain capacity. An …