Characterizing forest fire activity in Turkey by compound Poisson and time series models

Çekim, Hatice Öncel; Kadılar, Cem; Özel, Gamze

doi:10.1063/1.4825789

Cited by 2 publications

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“…Although the ARIMA method was first used by Box and Jenkins in 1970 [7], it still maintains its importance today [8]. The studies of Bodo et al [9], Bulligan et al [10], Zhigljavsky et al [11], Cekim et al [12] and Guarnaccia et al [13] have used the ARIMA method for modeling the series in various areas.…”

Section: Methodsmentioning

confidence: 99%

“…Bu amaçla, Box-Jenkins modellerinin uygulanabilmesi için serinin 1. dereceden fark ve 2. dereceden mevsimsel farkı alınarak seri durağan hale gelmiştir. Yapılan analizler sonucunda seriye en uygun model olarak SARIMA(1,1,1)(3,2,0) 12 modeli belirlenmiştir. Bu model kullanılarak endeks serisinin 2018 yılı için aylık öngörü değerleri hesaplanmıştır.…”

Section: öZetunclassified

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Examination of industry production index in Turkey with time series method

Çekim¹

2018

Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi

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In this paper, the time series analysis is conducted to the monthly industrial production index data calculated between 2005 and 2017 by TURKSTAT. The aim of the study is to define the industrial production index with the time series chart, to find the suitable time series model for the index and to forecast the future values of the index. For this purpose, we make the series stationary by taking both the first difference and the second seasonal difference of the series to perform the Box-Jenkins models. As a result of the analysis, SARIMA(1,1,1)(3,2,0) 12 model is determined as the most suitable model for the series. Using this model, the forecast values for the months of 2018 of the index series are calculated.

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Section: Methodsmentioning

confidence: 99%

Section: öZetunclassified

Examination of industry production index in Turkey with time series method

Çekim¹

2018

Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi

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Türkiye'nin Yanan Orman Alanının ARIMA Modeli ile Tahmini

Bagci

2023

Fırat Üniversitesi Sosyal Bilimler Dergisi

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Large-scale forest fires can cause significant ecological losses. Additionally, preserving forest areas may help to slow down climate change. Statistical models are one of the tools used in planning fire management strategies. In this study, the burned forest area of Turkey is modeled using the Auto-Regressive Integrated Moving Average (ARIMA) method following the identification, estimation, validation, and forecasting steps. As is known the ARIMA analysis is one of the popular techniques used in time series analysis. Annual total burned forest areas in Turkey over the period 1940-2021 are considered in the analysis. Three preliminary models are considered for evaluation of their modeling and prediction performances. The models' validities are investigated with Ljung–Box statistics, residual analysis, and cross-validation. According to the results, the ARIMA (3,1,0) model is found to be the most suitable model for predicting the future values of the burned forest area time series in Turkey. Forecasts for Turkey’s burned forest areas series are obtained for the next 3 years accordingly.

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Characterizing forest fire activity in Turkey by compound Poisson and time series models

Cited by 2 publications

References 0 publications

Examination of industry production index in Turkey with time series method

Examination of industry production index in Turkey with time series method

Türkiye'nin Yanan Orman Alanının ARIMA Modeli ile Tahmini

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