Nur Şebnem ERSÖZ, Pınar GÜNER, Ayhan AKBAŞ, Burcu BAKİR-GUNGOR

COMPARATIVE PERFORMANCE ANALYSIS OF ARIMA, PROPHET AND HOLT-WINTERS FORECASTING METHODS ON EUROPEAN COVID-19 DATA

COVID-19 son yılların en bulaşıcı hastalığıdır ve dünyanın her yerinde salgına neden olmuştur. Daha önce yüzlerce olan ölüm oranı önce binlere, sonra milyonlara yükselmiştir. Ocak 2020'den beri birçok bilim insanı, hükümetlerin hastanelerde yeterli düzenlemeleri yapabilmesi ve ölüm oranını azaltılabilmesi için COVID-19’un yayılımını anlamaya ve tahminlemeye çalışıyor. Bu araştırma makalesi, Avrupa’daki COVID-19 hastalık epidemiyolojisi için tahminler yapmak amacıyla, ARIMA, Prophet ve Holt Winters Üstel Düzeltme yöntemlerinin performans karşılaştırmasını sunmaktadır. Veri seti olarak, Dünya Sağlık Örgütü (DSÖ)'nün toplayıp kategorize ettiği, Avrupa ülkelerinin 2020 ile 2022 yılları arasındaki COVID-19 vaka verileri kullanılmıştır. Elde edilen sonuçlar, Holt-Winters Üstel Düzeltme (RMSE: 0.20, MAE: 0.17) yönteminin, ARIMA ve Prophet tahmin yöntemlerinden daha iyi performans gösterdiğini belirtmektedir.

Anahtar Kelimeler:

COVID-19, , Zaman Serisi Tahmini, , ARIMA, , Prophet, , Holt Winters Üstel Düzeltme

COMPARATIVE PERFORMANCE ANALYSIS OF ARIMA, PROPHET AND HOLT-WINTERS FORECASTING METHODS ON EUROPEAN COVID-19 DATA

COVID-19 is the most common infectious disease of the last few years and has caused an outbreak all around the world. The mortality rate, which was earlier in the hundreds, increased to thousands and then to millions. Since January 2020, several scientists attempted to understand and predict the spread of COVID-19 so that governments may make sufficient arrangements in hospitals and reduce the mortality rate. This research article presents a comparative performance analysis of ARIMA, Prophet and Holt-Winters Exponential Smoothing forecasting methods to make predictions for the COVID-19 disease epidemiology in Europe. The dataset has been collected from the World Health Organization (WHO) and includes the COVID-19 case data of European countries, which is categorized by WHO between the years of 2020 and 2022. The results indicate that Holt-Winters Exponential Smoothing method (RMSE: 0.2080, MAE: 0.1747) outperforms ARIMA and Prophet forecasting methods.

Keywords:

COVID-19, Time Series Forecasting, ARIMA, Prophet, Holt-Winters Exponential Smoothing,

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