Anomalies Prediction in Radon Time Series for Earthquake Likelihood Using Machine Learning-Based Ensemble Model

Anomalies Prediction in Radon Time Series for Earthquake Likelihood Using Machine Learning-Based Ensemble Model

The ability to predict the radioactive soil radon gas concentration is important for human beings because it serves as a precursor to earthquakes. Several studies have been conducted across the globe to confirm the correlation of radon emission dynamics and earthquakes, and concluded that the soil r...

Full description

Bibliographic Details
Main Authors: Adil Aslam Mir, Fatih Vehbi Celebi, Hadeel Alsolai, Shahzad Ahmad Qureshi, Muhammad Rafique, Jaber S. Alzahrani, Hany Mahgoub, Manar Ahmed Hamza
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Automated system
earthquakes
ensemble methods
percentage bias
soil radon gas
Online Access:https://ieeexplore.ieee.org/document/9745157/

Internet

https://ieeexplore.ieee.org/document/9745157/

Similar Items