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Artificial intelligence, machine learning, and deep learning in structural engineering: a scientometrics review of trends and best practices
Artificial Intelligence (AI), machine learning (ML), and deep learning (DL) are emerging
techniques capable of delivering elegant and affordable solutions which can surpass those …
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
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 …
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
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 …
engineering structures. This parameter is generally determined by conducting several tests …
ANN-based swarm intelligence for predicting expansive soil swell pressure and compression strength
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) …
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
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 …
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 …
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
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 …
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)
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 …
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
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 …
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
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 …
equipment. A reliable and accurate TBM performance (like penetration rate, PR) prediction …