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Journals / Süleyman Demirel Üniversitesi Fen Edebiyat Fakültesi Fen Dergisi / 2014 / Volume: 9 Issue: 2

Toprak Radon (222Rn) Gazı Anomalilerinin ARIMA Analizi

Miraç Kamışlıoğlu
Fatih Külahcı
Seçil Niksarlıoğlu
Pages
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Publication Date
2014-12-31
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The obtained results, ARIMA model is indicating success in predict subject

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Time series analysis, has wide applications in statistics, economics, physics and engineering such disciplines.
📊
Key Findings & Data:In this study, is formed a time series with soil radon gas (222Rn) measurements known as a pioneer of an earthquake.
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Conclusion & Impact:The obtained results, ARIMA model is indicating success in predict subject
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Zaman Serileri Analizi · Radon Gazı (222Rn) · ARIMA

Abstract

Time series analysis, has wide applications in statistics, economics, physics and engineering such disciplines. This method used for estimate correctly future values of the variables. In this study, is formed a time series with soil radon gas (222Rn) measurements known as a pioneer of an earthquake. Dynamic system modelling was performed with autoregressive (ARIMA) modelling process by used these measurements. ARIMA; time series analysis is modelled of the recoverable over time a random stochastic (probabilistic) process or its errors. ARIMA model is based on Box-Jenkins model. BoxJenkins model is a statistically based method which is used forward-looking forecasting and control of univariate time series. The obtained results, ARIMA model is indicating success in predict subject

Özet

Özet: Zaman serileri analizi, istatistik, ekonomi, fizik ve mühendislik gibi bilim dallarında geniş uygulama alanına sahiptir. Zaman serisi analizi, değişkenlerin gelecekteki değerlerinin doğru bir şekilde tahmin edilmesi için kullanılan bir yöntemdir. Bu çalışmada, bir deprem öncüsü olarak bilinen toprak radon gazı (222Rn) ölçümleri ile bir zaman serisi oluşturulmuştur. Bu veriler kullanılarak, otoregresif süreçler (ARIMA) yardımıyla dinamik sistem modellemesi yapılmıştır. ARIMA; zaman serileri analizinde, zaman içerisinde rastgele gerçekleşen bir stokastik (olasılıksal) sürecin veya hatalarının modellenmesidir. ARIMA modeli, temelde Box-Jenkins modeline dayanmaktadır. Box-Jenkins modeli, tek değişkenli zaman serilerinin ileriye dönük tahmin ve kontrolünde kullanılan istatistiksel tabanlı bir yöntemdir. Elde edilen sonuçlar, ARIMA modellerinin tahmin konusundaki başarısını göstermektedir. Anahtar kelimeler: Zaman Serileri Analizi, Radon Gazı (222Rn), ARIMA ARIMA Analysis of Soil Radon (222Rn) Gas Anomalies Abstract: Time series analysis, has wide applications in statistics, economics, physics and engineering such disciplines. This method used for estimate correctly future values of the variables. In this study, is formed a time series with soil radon gas (222Rn) measurements known as a pioneer of an earthquake. Dynamic system modelling was performed with autoregressive (ARIMA) modelling process by used these measurements. ARIMA; time series analysis is modelled of the recoverable over time a random stochastic (probabilistic) process or its errors. ARIMA model is based on Box-Jenkins model. Box-Jenkins model is a statistically based method which is used forward-looking forecasting and control of univariate time series. The obtained results, ARIMA model is indicating success in predict subject. Key words: Time Series Analysis, Radon Gas (222Rn), ARIMA

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Cite This Article

Kamışlıoğlu, M., Külahcı, F., Niksarlıoğlu, S. (2014). Toprak Radon (222Rn) Gazı Anomalilerinin ARIMA Analizi. Süleyman Demirel Üniversitesi Fen Edebiyat Fakültesi Fen Dergisi, Volume: 9 Issue: 2. https://ajindex.com/articles/1277996

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