[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] 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 …
[HTML][HTML] Artificial intelligence-enhanced non-destructive defect detection for civil infrastructure
As civil engineering projects become more complex, ensuring the integrity of infrastructure is
essential. Traditional inspection methods may damage structures, highlighting the need for …
essential. Traditional inspection methods may damage structures, highlighting the need for …
[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] Daily runoff forecasting using novel optimized machine learning methods
Accurate runoff forecasting is crucial for effective water resource management, yet existing
models often face challenges due to the complexity of hydrological systems. This study …
models often face challenges due to the complexity of hydrological systems. This study …
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 …
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] 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 …
Fatigue life prediction of corroded steel wires: An accurate and explainable data-driven approach
H Li, H Zhang, J Zhou, R **a, Y Gong, T Hu - Construction and Building …, 2024 - Elsevier
The fatigue performance of corroded steel wires significantly impacts bridge safety. Existing
methods have limited accuracy and generalizability due to varied experimental conditions …
methods have limited accuracy and generalizability due to varied experimental conditions …