Most public talk about AI focuses on large language models and flashy generative tools. But honestly, the most dependable ...

The two-stage AI framework for geopolymer concrete mix design significantly improves predictive accuracy, facilitating the ...

For decades, cardiovascular medicine has been a discipline of ‘averages’ and ‘thresholds’—relying on population-based risk ...

New research using AI-powered stacked ensemble models has improved accuracy in predicting NBA game results by combining multiple machine learning algorithms. These models not only forecast outcomes ...

ABSTRACT: Accurate prediction of survey response rates is essential for optimizing survey design and ensuring high-quality data collection. Traditional methods often struggle to capture the complexity ...

ABSTRACT: Accurate prediction of survey response rates is essential for optimizing survey design and ensuring high-quality data collection. Traditional methods often struggle to capture the complexity ...

The inversion of the one-dimensional wave spectrum from dual-polarized synthetic aperture radar (SAR) data is performed using machine learning methods, namely Random Forest (RF), eXtreme Gradient ...

Abstract: With growing popularity of electric cars (EVs) creates difficulty in power grid management. For the same, the prediction of EV charging demand is required. In this study, an ensemble ...

Researchers have developed a novel AI-driven framework using the XGBoost algorithm to accurately evaluate the skid resistance of asphalt pavements under various conditions. Published in Smart ...

Bacteriocins offer a promising solution to antibiotic resistance, possessing the ability to target a wide range of bacteria with precision. Thus, there is an urgent need for a computational model to ...

Accurate crop yield prediction is vital for ensuring global food security, particularly amid growing environmental challenges such as climate change. Although deep learning (DL) methods have shown ...