Radon (222 Rn) is a colourless, odourless, inert, and radioactive noble gas (t 1/2= 3.8 days)
that emanates from rocks and soils as a result of the alpha decay of its parent, radium (226 …

Artificial intelligence (AI) holds significant promise for advancing natural disaster
management through the use of predictive models that analyze extensive datasets, identify …

Many factors influence the accurate identification of radon anomalies triggered by
earthquakes to varying degrees. Therefore, this paper primarily provides a comprehensive …

Anomalies in soil radon (222 Rn) and thoron (220 Rn) time series data (TSD) have been
reported in many studies prior to earthquakes, suggesting both radioisotopes may serve as …

Earthquakes are the leading natural disasters that have caused loss of life and property
since the formation of the world. Machine learning and deep learning are frequently used in …

The present study reports measurements of radon in groundwater conducted in China
between January and December 2013. During the measurement period, a great M s= 6.6 …

In this study, we use the critical slowing down (CSD) theory to identify the precursory
anomalies of groundwater radon based on the 1000-day continuous data from 8 monitoring …

This study explores the potential of machine learning algorithms for earthquake prediction,
utilizing fluid chemical anomaly data from hot springs. Six hot springs, located within an …

Regression analysis is essential for prediction analysis and variable identification since air
pollution studies are complicated by competing suggestions and require careful …

Резюме Актуальность работы. Интерес к прогнозу землетрясений по-прежнему
актуален и исследования в этом направлении продолжаются. Изучено большое …