The machine learning algorithm and subsequent simulations are fueled by data, expert knowledge and statistical models ...

Oxygen depletion in the western Baltic Sea is not uncommon. Oxygen-poor conditions regularly occur in deeper waters, placing ...

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 ...

A Python implementation of the Truly Spatial Random Forests (SRF) algorithm for geoscience data analysis. Based on: Talebi, H., Peeters, L.J.M., Otto, A. & Tolosana-Delgado, R. (2022). A Truly Spatial ...

Class imbalance remains a critical challenge in machine learning, as it often leads to biased predictions where algorithms disproportionately favor the majority class, resulting in the ...

Monitoring of natural resources is a major challenge that remote sensing tools help to facilitate. The Sissili province in Burkina Faso is a territory that includes significant areas dedicated for the ...

Our planet’s forests are undergoing a transformation that researchers are only now beginning to fully understand. Between 2001 and 2020, scientists tracked dramatic shifts in how forests are managed ...

Abstract: A precise change detection in the multi-temporal optical images is considered as a crucial task. Although a variety of machine learning-based change detection algorithms have been proposed ...

The Internet of Things has proliferated, and the number of devices integrated into intelligent networks has made resource management and allocation one of the most critical challenges. The intrinsic ...

Abstract: The risk of pedestrian-involved traffic accidents represents a significant challenge to road safety and necessitates objective methods for analyzing the contributing factors. This study ...

Forest fires are on the rise globally. An increase in severe fire weather is largely responsible. By Rebecca Dzombak In 2023 and 2024, the hottest years on record, more than 78 million acres of ...

ABSTRACT: Missing data remains a persistent and pervasive challenge across a wide range of domains, significantly impacting data analysis pipelines, predictive modeling outcomes, and the reliability ...