Researchers have shown how random forest algorithms can be applied to complex ecological models to uncover the mechanisms driving system behavior. By analyzing a stage‑structured consumer‑resource ...

Afforestation—establishing forests on previously non-forested land, or where forests have not existed for a long time—is one of the nature-based and cost-effective solutions for climate change ...

Combining machine learning and feature selection, this research accurately predicts aluminum levels in marine environments, ...

Machine learning powers everything from streaming recommendations to medical image analysis. Knowing its core algorithms and uses can help you apply it in work and life. Here’s a clear, ...

The results show that the Decision Tree model emerged as the top-performing algorithm, achieving an accuracy rate of 99.36 percent. Random Forest followed closely with 99.27 percent accuracy, while ...

Read more about AI can’t deliver climate gains without strong governance and capacity building on Devdiscourse ...

A new AI tool detects pancreatic cancer up to three years early on routine CT scans, outperforming expert radiologists.

Methane is the second most important anthropogenic greenhouse gas after carbon dioxide, with a global warming potential roughly 28–34 times greater over a 100-year timescale. Major sources include ...

As atmospheric carbon dioxide levels continue to rise, accurately measuring the carbon stored in the world's forests has become more critical than ever. Forests are vital carbon sinks, but traditional ...

Discover how explainable AI enhances Parkinson’s disease prediction with improved accuracy and clinical interpretability.