Markov Chain transition probability modeling of radon gas records and future projection possibility determination. (March 2023)

• Record Type: Journal Article
• Authors: Bilici, Ahmet; Külahcı, Fatih; Bilici, Sevim; Şen, Zekâi
• Is Part Of: Journal of atmospheric and solar-terrestrial physics. Volume 244(2023)
• Publication Date: 2023-03
• Subjects: Markov chain simulation -- Radon -- Transition -- Probability -- Category -- Projection; Geophysics -- Periodicals; Atmospheric physics -- Periodicals; Géophysique -- Périodiques; Météorologie physique -- Périodiques; Electronic journals; 551.51
• DOI: 10.1016/j.jastp.2023.106027
• Languages: English
• ISSNs: 1364-6826

Abstract

Abstract: Markov Chain models serve two purposes firstly, subdivide the main data based on the mean value and one and two standard deviation plus and minus values around the mean value. The second stage of modeling, after calculating the transition probabilities between these categories from the available data, is completed by repeatedly multiplying the categorization date groups until the steady-state transition probability values are obtained. This procedure provides a convenient modeling approach for radon gas transient measurement records. After a brief presentation of Markov Chain procedure in this paper, the application is carried out by considering five categories that lead to a better transition probability matrix. Such a matrix provides information about the probabilities of future transition at the radon data measuring station. In addition, it is possible to associate these transition probabilities with the possibility of an earthquake. Graphical abstract: Image 1 Highlights: Markov Chain Simulation model is obtained for radon gas emission from soil. ArTificial intelligence applications for soil Rn release in relation to earthquakes. Results are obtained with approximately 5 years (1785 days) of Radon gas release.