[HTML][HTML] Eco-friendly mix design of slag-ash-based geopolymer concrete using explainable deep learning
Geopolymer concrete is a sustainable and eco-friendly substitute for traditional OPC
(Ordinary Portland Cement) based concrete, as it reduces greenhouse gas emissions. With …
(Ordinary Portland Cement) based concrete, as it reduces greenhouse gas emissions. With …
Modeling streamflow in non-gauged watersheds with sparse data considering physiographic, dynamic climate, and anthropogenic factors using explainable soft …
C Madhushani, K Dananjaya, IU Ekanayake… - Journal of …, 2024 - Elsevier
Streamflow forecasting is essential for effective water resource planning and early warning
systems. Streamflow and related parameters are often characterized by uncertainties and …
systems. Streamflow and related parameters are often characterized by uncertainties and …
[HTML][HTML] A new frontier in streamflow modeling in ungauged basins with sparse data: A modified generative adversarial network with explainable AI
U Perera, DTS Coralage, IU Ekanayake… - Results in …, 2024 - Elsevier
Streamflow forecasting is crucial for effective water resource planning and early warning
systems, especially in regions with complex hydrological behaviors and uncertainties. While …
systems, especially in regions with complex hydrological behaviors and uncertainties. While …
[HTML][HTML] An explainable machine learning approach to predict the compressive strength of graphene oxide-based concrete
Graphene oxide (GO) has shown promise in improving concrete strength. Despite its
frequent use in cement composites, its effect on concrete properties is less explored. The …
frequent use in cement composites, its effect on concrete properties is less explored. The …
Intelligent evaluation of interference effects between tall buildings based on wind tunnel experiments and explainable machine learning
K Wang, J Liu, Y Quan, Z Ma, J Chen, Y Bai - Journal of Building …, 2024 - Elsevier
The interference effects of taller high-rise buildings significantly impact the nearby shorter
high-rise buildings in dense urban areas, potentially leading to severe wind-induced …
high-rise buildings in dense urban areas, potentially leading to severe wind-induced …
[HTML][HTML] Effect of endogenous and anthropogenic factors on the alkalinisation and salinisation of freshwater in United States by using explainable machine learning
ND Wimalagunarathna, G Dharmarathne… - Case Studies in …, 2024 - Elsevier
Freshwater salinisation and alkalinisation strongly depend on human and natural factors.
We used an explainable machine learning approach to investigate the impact of natural and …
We used an explainable machine learning approach to investigate the impact of natural and …
The prediction on non-Gaussian characteristics of wind pressure for the long-span roof in the mountainous area using proper orthogonal decomposition–deep …
X Zhang, C Pei, M Liu, X Yang, X Cheng - Physics of Fluids, 2024 - pubs.aip.org
To make an accurate prediction of the non-Gaussian characteristics of wind pressure for the
long-span roof, this study combines the proper orthogonal decomposition (POD) technique …
long-span roof, this study combines the proper orthogonal decomposition (POD) technique …
Extrapolating low-occurrence strong wind speeds at pedestrian levels using artificial neural networks trained by a single turbulent dataset
Predicting low-occurrence strong wind speeds in urban areas is crucial for enhancing the
comfort and ensuring the safety of residents. Artificial neural network (ANN) models …
comfort and ensuring the safety of residents. Artificial neural network (ANN) models …
[HTML][HTML] Comparative study on deep and machine learning approaches for predicting wind pressures on tall buildings
Wind-structures interaction has been extensively examined in the last few decades using
field measurements, full scale measurements and wind tunnel testing. These experimental …
field measurements, full scale measurements and wind tunnel testing. These experimental …
[HTML][HTML] An efficient computational investigation on accurate daily soil temperature prediction using boosting ensemble methods explanation based on SHAP …
Accurately predicting soil temperature (Ts) serves as the foundation of geothermal
applications, modern irrigation strategies in arid agricultural landscapes, and understanding …
applications, modern irrigation strategies in arid agricultural landscapes, and understanding …