Artificial intelligence, machine learning, and deep learning in structural engineering: a scientometrics review of trends and best practices

ATG Tapeh, MZ Naser - Archives of Computational Methods in …, 2023 - Springer
Artificial Intelligence (AI), machine learning (ML), and deep learning (DL) are emerging
techniques capable of delivering elegant and affordable solutions which can surpass those …

Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance

A Merghadi, AP Yunus, J Dou, J Whiteley… - Earth-Science …, 2020 - Elsevier
Landslides are one of the catastrophic natural hazards that occur in mountainous areas,
leading to loss of life, damage to properties, and economic disruption. Landslide …

A novel hybrid extreme learning machine–grey wolf optimizer (ELM-GWO) model to predict compressive strength of concrete with partial replacements for cement

M Shariati, MS Mafipour, B Ghahremani… - Engineering with …, 2022 - Springer
Compressive strength of concrete is one of the most determinant parameters in the design of
engineering structures. This parameter is generally determined by conducting several tests …

ANN-based swarm intelligence for predicting expansive soil swell pressure and compression strength

FE Jalal, M Iqbal, WA Khan, A Jamal, K Onyelowe… - Scientific Reports, 2024 - nature.com
This research suggests a robust integration of artificial neural networks (ANN) for predicting
swell pressure and the unconfined compression strength of expansive soils (P s UCS-ES) …

The effect of carbon dioxide emissions on the building energy efficiency

J Min, G Yan, AM Abed, S Elattar, MA Khadimallah… - Fuel, 2022 - Elsevier
During this anthropocentric period, sustainable energy supply and climate changing could
be a main source of problem for human being. Scientists believe that the ratio of climate …

Dynamic stability/instability simulation of the rotary size-dependent functionally graded microsystem

X Huang, H Hao, K Oslub, M Habibi… - Engineering with …, 2022 - Springer
In the current paper, vibrational and critical circular speed characteristics of a functionally
graded (FG) rotary microdisk is examined considering a continuum nonlocal model called …

[HTML][HTML] Estimating compressive strength of lightweight foamed concrete using neural, genetic and ensemble machine learning approaches

BA Salami, M Iqbal, A Abdulraheem, FE Jalal… - Cement and Concrete …, 2022 - Elsevier
Foamed concrete is special not only in terms of its unique properties, but also in terms of its
challenging compositional mixture design, which necessitates multiple experimental trials …

Prediction of concrete strength in presence of furnace slag and fly ash using Hybrid ANN-GA (Artificial Neural Network-Genetic Algorithm)

M Shariati, MS Mafipour, P Mehrabi, M Ahmadi… - Smart structures and …, 2020 - dbpia.co.kr
Mineral admixtures have been widely used to produce concrete. Pozzolans have been
utilized as partially replacement for Portland cement or blended cement in concrete based …

Hybridization of metaheuristic algorithms with adaptive neuro-fuzzy inference system to predict load-slip behavior of angle shear connectors at elevated temperatures

M Shariati, SM Davoodnabi, A Toghroli, Z Kong… - Composite structures, 2021 - Elsevier
Abstract Steel-Concrete Composite floor systems are one of the essential components in the
construction industry. Recent studies have shown that fire-induced problems damage shear …

A new hybrid grey wolf optimizer-feature weighted-multiple kernel-support vector regression technique to predict TBM performance

H Yang, Z Wang, K Song - Engineering with Computers, 2022 - Springer
Full-face tunnel boring machine (TBM) is a modern and efficient tunnel construction
equipment. A reliable and accurate TBM performance (like penetration rate, PR) prediction …