Methane is one of the most powerful greenhouse gases, yet quantifying its emissions remains difficult at large scales.

Abstract: With the improvement of computer computing power, machine learning such as random forests, extreme gradient boosting, and support vector machines have ushered in many optimizations and ...

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 ...

Background: Quantifying aboveground biomass (AGB) is crucial for studying the carbon cycle and estimating mitigation potential of climate change. Combining field inventory data and remote sensing such ...

Abstract: The research introduces a methodology to predict the flexural behavior of a laminate before conducting any experimental tests. To derive such a model, an artificial intelligence (AI)-based ...