Yeşim DOKUZ, Aslı BOZDAĞ, Öznur Begüm GÖKÇEK

HAVA KALİTESİ PARAMETRELERİNİN TAHMİNİ VE MEKANSAL DAĞILIMI İÇİN MAKİNE ÖĞRENMESİ YÖNTEMLERİNİN KULLANILMASI

Hava kirliliği, nüfus ve endüstrileşmenin artması ile birlikte günümüzde küresel boyutta yaşanan sorunlardan biri haline gelmiştir. Bu nedenle hava kirletici parametreler düzenli aralıklarla ölçülmeli ve ölçüm sonuçları değerlendirilerek gerekli tedbirler alınmalıdır. Hava kirliliğinin önlenmesi amacıyla kirletici parametreler bir model kapsamında değerlendirilmesi gerekmektedir. Son zamanlarda günümüzde hava kirliliğine yönelik objektif ve daha hassas sonuçların elde edilmesi için yapay zeka teknolojilerine ait makine öğrenmesi algoritmalarından yararlanılarak elde edilen çalışmalar yapılmaktadır. Bu çalışmada, öncelikli olarak hava kirletici parametrelerin özellikleri, çevreye olan etkileri ve bu parametrelerin tahmin edilmesi ve izlenmesinin gerekliliği açıklanmıştır. Ardından bu parametrelerin değerlendirilmesinde uygulanan makine öğrenmesi yöntemlerinin neler olduğu; hangi parametrelerin kullanıldığı, kullanım amaçları, kısıtlılıkları ve elde edilen doğruluk düzeyleri açısından incelenerek kullanılan yöntemlere ve çalışma prensiplerine ilişkin detaylı bilgi verilmiştir. Bu çalışma, hava kalitesinin iyileştirilerek sürdürülebilir bir çevrenin elde edilmesinde hangi parametreler hangi yöntem kullanılarak nasıl bir analiz ile incelenmeli sorusuna ilişkin seçim karmaşasının çözümlenmesine yönelik gelecek çalışmalara bir fikir sunmaktadır.

Anahtar Kelimeler:

hava kirletici parametre, makine öğrenmesi, mekansal dağılım, yapay zeka, tahmin modellemesi

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