Shear strength prediction of reinforced concrete beams using machine learning

MS Sandeep, K Tiprak, S Kaewunruen, P Pheinsusom… - Structures, 2023 - Elsevier
Recent years have witnessed a surge in the application of machine learning techniques for
solving hard to solve structural engineering problems. The application of machine learning …

Artificial neural networks applications in construction and building engineering (1991–2021): science mapping and visualization

M Marzouk, A Elhakeem, K Adel - Applied Soft Computing, 2024 - Elsevier
Artificial neural network (ANN) has acquired noticeable interest from the research
community to handle complex problems in Construction and Building engineering (CB). This …

Predicting concrete compressive strength using hybrid ensembling of surrogate machine learning models

PG Asteris, AD Skentou, A Bardhan, P Samui… - Cement and Concrete …, 2021 - Elsevier
This study aims to implement a hybrid ensemble surrogate machine learning technique in
predicting the compressive strength (CS) of concrete, an important parameter used for …

A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength

DJ Armaghani, PG Asteris - Neural Computing and Applications, 2021 - Springer
Despite the extensive use of mortars materials in constructions over the last decades, there
is not yet a reliable and robust method, available in the literature, which can estimate its …

Machine learning models for predicting the compressive strength of concrete containing nano silica

A Garg, P Aggarwal, Y Aggarwal… - Computers and …, 2022 - koreascience.kr
Experimentally predicting the compressive strength (CS) of concrete (for a mix design) is a
time-consuming and laborious process. The present study aims to propose surrogate …

A novel artificial intelligence technique to predict compressive strength of recycled aggregate concrete using ICA-XGBoost model

J Duan, PG Asteris, H Nguyen, XN Bui… - Engineering with …, 2021 - Springer
Recycled aggregate concrete is used as an alternative material in construction engineering,
aiming to environmental protection and sustainable development. However, the …

Prediction of cement-based mortars compressive strength using machine learning techniques

PG Asteris, M Koopialipoor, DJ Armaghani… - Neural Computing and …, 2021 - Springer
The application of artificial neural networks in mapping the mechanical characteristics of the
cement-based materials is underlined in previous investigations. However, this machine …

Prediction of heating and cooling loads based on light gradient boosting machine algorithms

J Guo, S Yun, Y Meng, N He, D Ye, Z Zhao, L Jia… - Building and …, 2023 - Elsevier
Abstract Machine learning models have been widely used to study the prediction of heating
and cooling loads in residential buildings. However, most of these methods use the default …

Prediction of axial load capacity of rectangular concrete-filled steel tube columns using machine learning techniques

TT Le, PG Asteris, ME Lemonis - Engineering with Computers, 2022 - Springer
This work aims to develop a novel and practical equation for predicting the axial load of
rectangular concrete-filled steel tubular (CFST) columns based on soft computing …

A sensitivity and robustness analysis of GPR and ANN for high-performance concrete compressive strength prediction using a Monte Carlo simulation

DV Dao, H Adeli, HB Ly, LM Le, VM Le, TT Le… - Sustainability, 2020 - mdpi.com
This study aims to analyze the sensitivity and robustness of two Artificial Intelligence (AI)
techniques, namely Gaussian Process Regression (GPR) with five different kernels …