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

The absence of reliable data on fundamental economic indicators (e.g. real GDP), combined with structural shifts in the economy, can severely constrain the ability to conduct accurate macroeconomic ...

Stock markets are essential for households for wealth creation and for firms for raising financial resources for capacity ...

While demand planning accuracy currently hovers around 60%, DLA officials aim to push that baseline figure to 85% with the help of AI and ML tools. Improved forecasting will ensure the services have ...

AI models can process thousands of factors simultaneously, including demand signals across multiple items, macroeconomic indicators and real-time marketplace trends.

As climate extremes intensify across Africa, the need for accurate and timely weather prediction has become increasingly urgent. Floods, heatwaves, droughts, and air pollution events are placing a ...

Tropical cyclones remain one of the most formidable natural hazards, intricately governed by a complex interplay of atmospheric and oceanic processes. Recent advancements have enhanced our ...

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...