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 …

Predicting the compressive strength of concrete containing metakaolin with different properties using ANN

MJ Moradi, M Khaleghi, J Salimi, V Farhangi… - Measurement, 2021 - Elsevier
The advantages of using Metakaolin (MK) as a supplementary cementitious material have
led this highly active pozzolan to be widely used in the concrete industry. Awareness of the …

[HTML][HTML] Compressive strength of concrete containing furnace blast slag; optimized machine learning-based models

M Kioumarsi, H Dabiri, A Kandiri, V Farhangi - Cleaner Engineering and …, 2023 - Elsevier
Abstract Replacing Ordinary Portland Cement (OPC) with industrial waste like Ground
Granulated Blast Furnace Slag (GGBFS) has been proven to have remarkable benefits …

The prediction of fire performance of concrete-filled steel tubes (CFST) using artificial neural network

MJ Moradi, K Daneshvar, D Ghazi-Nader… - Thin-Walled Structures, 2021 - Elsevier
Search for enhancing the efficiency has led to composite structures such as concrete-filled
steel tubes (CFST) with increasing applications across the world. The fire performance of …

Predicting compressive strength of concrete containing recycled aggregate using modified ANN with different optimization algorithms

A Kandiri, F Sartipi, M Kioumarsi - Applied Sciences, 2021 - mdpi.com
Using recycled aggregate in concrete is one of the best ways to reduce construction
pollution and prevent the exploitation of natural resources to provide the needed aggregate …

Application of artificial intelligence in predicting the residual mechanical properties of fiber reinforced concrete (FRC) after high temperatures

V Farhangi, MJ Moradi, K Daneshvar… - Construction and Building …, 2024 - Elsevier
The practical application of Artificial Intelligence (AI) approaches in estimating the
mechanical properties of fiber-reinforced concrete (FRC) subjected to high temperatures …

Predicting the compressive strength of concrete containing binary supplementary cementitious material using machine learning approach

N Moradi, MH Tavana, MR Habibi, M Amiri, MJ Moradi… - Materials, 2022 - mdpi.com
Several advantages of supplementary cementitious materials (SCMs) have led to
widespread use in the concrete industry. Many various SCMs with different characteristics …

A new RBF neural network-based fault-tolerant active control for fractional time-delayed systems

B Wang, H Jahanshahi, C Volos, S Bekiros, MA Khan… - Electronics, 2021 - mdpi.com
Recently, intelligent control techniques have received considerable attention. In most
studies, the systems' model is assumed to be without any delay, and the effects of faults and …

Effects of impact loads on heated-and-cooled reinforced concrete slabs

K Daneshvar, MJ Moradi, M Khaleghi, M Rezaei… - Journal of Building …, 2022 - Elsevier
The potential collapse of heavy components in fires can cause dynamic loads on slabs
triggering a progressive collapse of weakened slabs on lower floors. In this study, three …

Application of machine learning to predict the mechanical characteristics of concrete containing recycled plastic-based materials

S Rezvan, MJ Moradi, H Dabiri, K Daneshvar… - Applied Sciences, 2023 - mdpi.com
One of the practical ways to overcome the adverse environmental effects of plastic bottle
waste is to implement bottles into concrete, one of the most widely used materials in the …