In the fall of 2022, hurricanes Ian and Nicole struck Florida’s east coast within six weeks of one another, bringing intense rainfall, storm surges and coastal erosion. In the immediate aftermath, ...

Explore the evolution of Random Number Generators and how modern algorithmic transparency is reshaping user trust in ...

Indonesia experiences massive forest fires as the dry season approaches. They are a major environmental challenge because ...

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

This research introduces a multi-resolution exploration method, enhancing robotic navigation efficiency and adaptability in ...

Afforestation—establishing forests on previously non-forested land, or where forests have not existed for a long time—is one ...

Pradhan and Basab Chakraborty, has developed a grey wolf optimisation (GWO)-based hybrid regression model that significantly improves state-of-health (SOH) estimation for bipolar lead-acid batteries.

Figures 12-14 are the land use/land cover maps of existing forest reserves in the FCT, namely; Tufa in Abaji, Chihuma, Chikwei, Kusoru and Shaba in Bwari, Maje Abuchi in Gwagwalada, then, Buga Hill, ...

An intelligent monitoring pipe combines optical sensing with machine learning algorithms to monitor and predict 3D soil settlement, which could help provide early warnings of risks from soil ...

As atmospheric carbon dioxide levels continue to rise, accurately measuring the carbon stored in the world's forests has ...

Random forest regression is a tree-based machine learning technique to predict a single numeric value. A random forest is a collection (ensemble) of simple regression decision trees that are trained ...