Turkiye Klinikleri Journal of Biostatistics

.: ORIGINAL RESEARCH
Statistical Comparison of the Impacts of Weather Variables and Particulate Matter on Bacterial Density: Methodological Research
Hava Değişkenleri ve Partikül Maddenin Bakteri Yoğunluğu Üzerindeki Etkilerinin İstatistiksel Karşılaştırılması: Metodolojik Araştırma
Betül KAN KILINÇa, Büşra ERGİNb, Meral YILMAZ CANKILIÇb
aDepartment of Statistics, Eskişehir Technical University Faculty of Science, Eskişehir, TURKEY
bDepartment of Biology, Eskişehir Technical University Faculty of Science, Eskişehir, TURKEY
Turkiye Klinikleri J Biostat. 2021;13(3):273-81
doi: 10.5336/biostatic.2021-85470
Article Language: EN
Full Text
ABSTRACT
 Objective: In this study, the number of bacteriae in the air at five different regions in Eskişehir (Turkey) according to the settle plate method and some meteorological factors such as temperature and relative humidity were collected and analyzed statistically. The data were used to predict the amount of bacteriae using machine learning algorithms. Material and Methods: Air samples were taken from specified sampling points using the settle plate method. The random forest method, multivariate adaptive regression splines, support vector machine and ordinary least squares models were employed to analyze a qualified data set collected through 5 different monitoring locations in Eskişehir city, Turkey. All analyses were conducted using RStudio Software (version 1.2.1335). Results: The results revealed that all variables including weather characteristics and particulate matters were found statistically significant on the amount of the bacteria. Among modeling methods, the random forest model overperformed the others in terms of root mean square. Conclusion: Results might be useful for researchers studying bacterial density. These findings may provide policy-makers with crucial information for a better climate and health policy development, which helps address the conflict between development and air pollution, may be applicable in Turkey and other countries as well.

Keywords: Bacteria; particulate matter; random forest method; statistical modelling
ÖZET
 Amaç: Bu çalışmada, Eskişehir (Türkiye) ilinde 5 farklı bölgede petri kapları kullanılarak; bakteri miktarları, sıcaklık, nem vb. bazı meteorolojik değerler elde edilmiş ve istatistiksel olarak analiz edilmiştir. Elde edilen verilerdeki bakteri miktarı, makine öğrenimi algoritmalarından bazıları kullanılarak tahmin edilmiştir. Gereç ve Yöntemler: Petri kabı yöntemi kullanılarak belirlenen örnekleme noktalarından hava örnekleri alınmıştır. Rastgele orman algoritması, çoklu adaptif regresyon eğrileri, destek vektör makinesi ve sıradan en küçük kareler yöntemleri, Eskişehir'deki 5 farklı bölgeden toplanan verileri analiz etmek için kullanılmıştır. Bütün analiz ve hesaplamalarda RStudio kullanılmıştır (versiyon 1.2.1335). Bulgular: Sonuçlar incelendiğinde, bütün değişkenlerin; çevre faktörlerin ve kirleticilerin, bakteri yoğunluğu üzerindeki etkisi istatistiksel olarak anlamlı bulunmuştur. Yöntemler arasında, hata kareler ortalamasının karekökü kullanılarak seçim yapıldığında rastgele orman algoritması en iyi sonucu vermiştir. Sonuç: Bu sonuçlar bakteri miktarı çalışan araştırmacılar için ileride yararlı olabilir. Bulgular, politika yapıcılara daha iyi iklimlendirme ve sağlık politikası geliştirme için önemli bilgiler sağlayabilir; kalkınma ile hava kirliliği arasındaki çatışmayı çözmeye yardımcı olabilir, benzer koşullar görülen diğer şehir ve ülkelerde de uygulanabilir.

Anahtar Kelimeler: Bakteri; partikül madde; rastgele orman modeli; istatistiksel modelleme
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