[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 strength characteristics of basalt fiber reinforced concrete using multiple explainable machine learning with a graphical user interface
This study investigated the importance of applying explainable artificial intelligence (XAI) on
different machine learning (ML) models developed to predict the strength characteristics of …
different machine learning (ML) models developed to predict the strength characteristics of …
[HTML][HTML] Advancing water quality assessment and prediction using machine learning models, coupled with explainable artificial intelligence (XAI) techniques like …
Water quality assessment and prediction play crucial roles in ensuring the sustainability and
safety of freshwater resources. This study aims to enhance water quality assessment and …
safety of freshwater resources. This study aims to enhance water quality assessment and …
[HTML][HTML] A novel explainable AI-based approach to estimate the natural period of vibration of masonry infill reinforced concrete frame structures using different machine …
P Thisovithan, H Aththanayake, DPP Meddage… - Results in …, 2023 - Elsevier
In this study, we used four different machine learning models-artificial neural network (ANN),
support vector regression (SVR), k-nearest neighbor (KNN), and random forest (RF)-to …
support vector regression (SVR), k-nearest neighbor (KNN), and random forest (RF)-to …
[HTML][HTML] Adapting cities to the surge: A comprehensive review of climate-induced urban flooding
Climate change is a serious global issue causing more extreme weather patterns, resulting
in more frequent and severe events like urban flooding. This review explores the connection …
in more frequent and severe events like urban flooding. This review explores the connection …
[HTML][HTML] Evaluating expressway traffic crash severity by using logistic regression and explainable & supervised machine learning classifiers
The number of expressway road accidents in Sri Lanka has significantly increased (by 20%)
due to the expansion of the transport network and high traffic volume. It is crucial to identify …
due to the expansion of the transport network and high traffic volume. It is crucial to identify …
Modeling streamflow in non-gauged watersheds with sparse data considering physiographic, dynamic climate, and anthropogenic factors using explainable soft …
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 novel machine learning approach for diagnosing diabetes with a self-explainable interface
This study introduces the first-ever self-explanatory interface for diagnosing diabetes
patients using machine learning. We propose four classification models (Decision Tree (DT) …
patients using machine learning. We propose four classification models (Decision Tree (DT) …
Daily streamflow forecasting in mountainous catchment using XGBoost, LightGBM and CatBoost
R Szczepanek - Hydrology, 2022 - mdpi.com
Streamflow forecasting in mountainous catchments is and will continue to be one of the
important hydrological tasks. In recent years machine learning models are increasingly used …
important hydrological tasks. In recent years machine learning models are increasingly used …
[HTML][HTML] Predicting adhesion strength of micropatterned surfaces using gradient boosting models and explainable artificial intelligence visualizations
Fibrillar dry adhesives are widely used due to their effectiveness in air and vacuum
conditions. However, their performance depends on various factors. Previous studies have …
conditions. However, their performance depends on various factors. Previous studies have …