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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 …
[HTML][HTML] A technical review of computational fluid dynamics (CFD) applications on wind design of tall buildings and structures: Past, present and future
Over the past two decades, an upsurge in using Computational Fluid Dynamics (CFD) for
wind design on tall buildings has been observed. An extensive amount of work has been …
wind design on tall buildings has been observed. An extensive amount of work has been …
Wind energy system for buildings in an urban environment
Urban built environments have grown dramatically worldwide in the past few decades due to
rapid economic and population growths. The potential utilization of renewable resources is …
rapid economic and population growths. The potential utilization of renewable resources is …
Applicability analysis of transformer to wind speed forecasting by a novel deep learning framework with multiple atmospheric variables
Accurate wind speed forecasting plays a crucial role in the efficient and economical
management of power supply systems. In this study, a novel framework combining …
management of power supply systems. In this study, a novel framework combining …
Automatic diagnosis of COVID-19 with MCA-inspired TQWT-based classification of chest X-ray images
In this era of Coronavirus disease 2019 (COVID-19), an accurate method of diagnosis with
less diagnosis time and cost can effectively help in controlling the disease spread with the …
less diagnosis time and cost can effectively help in controlling the disease spread with the …
[HTML][HTML] Explainable Machine Learning (XML) to predict external wind pressure of a low-rise building in urban-like settings
This study used explainable machine learning (XML), a new branch of Machine Learning
(ML), to elucidate how ML models make predictions. Three tree-based regression models …
(ML), to elucidate how ML models make predictions. Three tree-based regression models …
Green building practices to integrate renewable energy in the construction sector: a review
L Chen, Y Hu, R Wang, X Li, Z Chen, J Hua… - Environmental …, 2024 - Springer
The building sector is significantly contributing to climate change, pollution, and energy
crises, thus requiring a rapid shift to more sustainable construction practices. Here, we …
crises, thus requiring a rapid shift to more sustainable construction practices. Here, we …
Applications of machine learning to wind engineering
Advances of the analytical, numerical, experimental and field-measurement approaches in
wind engineering offers unprecedented volume of data that, together with rapidly evolving …
wind engineering offers unprecedented volume of data that, together with rapidly evolving …
Assessing wind field characteristics along the airport runway glide slope: An explainable boosting machine-assisted wind tunnel study
Aircraft landings are especially perilous when the wind is gusty near airport runways. For
this reason, an aircraft may deviate from its glide slope, miss its approach, or even crash in …
this reason, an aircraft may deviate from its glide slope, miss its approach, or even crash in …
Interpretation of machine-learning-based (black-box) wind pressure predictions for low-rise gable-roofed buildings using Shapley additive explanations (SHAP)
Conventional methods of estimating pressure coefficients of buildings retain time and cost
constraints. Recently, machine learning (ML) has been successfully established to predict …
constraints. Recently, machine learning (ML) has been successfully established to predict …