Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Interpretable AI model could offer new insights into why medicines cause certain side effects, helping to improve future drug safety predictions.

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

The IT team at North-Eastern Hill University has launched an innovative AI-driven landslide mapping tool specifically for Meghalaya. Utilizing an impressive combination of ten machine learning ...

Ensemble integrating three architectures achieved area under the curve of 0.9208, outperforming individual models ...

Researchers have developed a powerful machine learning framework that can accurately predict and optimize biochar production from algae, offering a ...

This paper presents a novel framework for optimizing Carbon Release (CR) through an AI-driven approach to Fossil Fuel Intake (FFI) management. We propose a new training methodology for AI models to ...

Artificial intelligence is reshaping cybersecurity, but much of that progress has focused on cloud and enterprise ...

According to A Survey of AI-Enabled Predictive Maintenance for Railway Infrastructure: Models, Data Sources, and Research Challenges, published in Sensors, AI-based predictive maintenance systems ...

India’s ability to predict cyclones has improved markedly, with measurable gains in forecast accuracy for cyclone track, ...

For example, a Convolutional Neural Network (CNN) trained on thousands of radar echoes can recognize the unique spatial signature of a small metallic fragment, even when its signal is partially masked ...