The lack of maps depicting forest three-dimensional structure, particularly as pertaining to
snags and understory shrub species distribution, is a major limitation for managing wildlife …

In recent years, there has been growing interest in using precipitable water vapor (PWV)
derived from global positioning system (GPS) signal delays to predict rainfall. However, the …

The present study aims to investigate the potential of the random forests ensemble
classification and regression technique to improve rainfall rate assignment during day, night …

Purpose: In an era of unprecedented student measurement and emphasis on data-driven
educational decision making, the full potential for using data to target resources to students …

Drinking water concentrations of per-and polyfluoroalkyl substances (PFAS) exceed
provisional guidelines for millions of Americans. Data on private well PFAS concentrations …

Sports analytics (SA) incorporate machine learning (ML) techniques and models for
performance prediction. Researchers have previously evaluated ML models applied on a …

Data Mining is processed in order to help policy makers for giving valid and efficient
decisions using the available data on the subject. In general, data mining has descriptive …

A new rainfall retrieval technique for determining rainfall rates in a continuous manner (day,
twilight, and night) resulting in a 24-h estimation applicable to midlatitudes is presented. The …

Nowcasting of severe weather events and summer storms, in particular, are intensively
studied as they have great potential for large economic and societal losses. Use of Global …

In this study, the strength and reliability of internal accuracy estimate built in random forest
(RF) ensemble classifier was evaluated. Specifically, we compared the reliability of the …