Nevşehir İli Hava Kalitesinin Markov Zinciri ile Tahmini

Bu makalede Nevşehir İlinde µg m-3 seviyesinde bulunan PM10, SO2, CO, NO2 ve O3 gibi temel hava kirletici parametreleri 01.08.2019-19.11.2020 tarihleri arasında izlenilmiş ve bu parametrelere bağlı olarak Hava Kalite İndeksi (HKİ) değerleri hesaplanmıştır. Nevşehir İli HKİ değerleri iyi ve hassas dereceler arasında değişkenlik göstermektedir. HKİ izleme verileri kullanılarak Küçük Ölçekli ve Ayrık Zamanlı Markov Zinciri Modelleri eğitilmiş ve 20.11.2020-20.12.2020 tarihlerini kapsayan yeni verilerle doğrulamaları yapılmıştır. Yapılan bu çalışmada Nevşehir İli HKİ değerleri, Küçük Ölçekli ve Ayrık Zamanlı Markov zincir modelleri ile sırasıyla 0,887 ve 0,982 oranında başarıyla tahmin edilmiştir. Nevşehir İli hava kalitesine bağlı olarak daha az değişken duruma sahip olan Ayrık-Zamanlı Markov Zinciri Modeli hem eğitimde hem de kontrolünde kullanılan HKİ verilerini tahmin etmede daha başarılı bulunmuştur. Sonuç olarak Markov Zinciri modellerinin farklı hava koşullarını tahmin etmede başarılı bir yöntem olarak kullanılabileceği belirlenmiştir.

Prediction of Nevşehir Province Air Quality with Markov Chain

In this article, basic air pollutant parameters such as PM10, SO2, CO, NO2, and O3 at µg m-3 level in Nevşehir Province were monitored between 01.08.2019-19.11.2020 and Air Quality Index (AQI) values were calculated depending on these parameters. Nevşehir Province AQI values vary between good and sensitive degrees. While monitoring data were used in the training of the models, the data calculated between 20.11.2020-20.12.2020 and not used in the training of the models were also used in the checking. In this study, Nevşehir Province AQI values were successfully predicted using small-scale and discrete-time Markov Chain Models at 0.887 and 0.982, respectively. The discrete-time Markov Chain Model, which has less variable status depending on the air quality of Nevşehir Province, has been found to be more successful in predicting the AQI data used both in training and checking. As a result, it has been revealed that Markov Chain models can be used as a successful method to predict different weather conditions.

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Düzce Üniversitesi Bilim ve Teknoloji Dergisi-Cover
  • Yayın Aralığı: Yılda 4 Sayı
  • Başlangıç: 2013
  • Yayıncı: Düzce Üniversitesi Fen Bilimleri Enstitüsü