Araştırma Makalesi
İSTANBUL İLİ TROPSOFERİK OZON (O3) KONSANTRASYONLARININ HÜCRESEL YAPAY SİNİR AĞ YÖNTEMİYLE MODELLENMESİ
Öz
Son yıllarda özellikle büyük şehirlerde, artan nüfus ve endüstrileşmeyle fotokimyasal smog oluşumu da
artmaktadır. Fotokimyasal smog oluşumunda en önemli kirletici ozon gazıdır. Bu yüzden pek çok çalışma ozon ve ozon öncülerini hesaba katan hava kalitesi modellemesi üzerinde yoğunlaşmaktadır. Bu çalışmada 6 farklı kirletici parametre ve 8 meteorolojik faktör dikkate alınarak, İstanbul ili troposferik ozon konsantrasyonları Hücresel Yapay Sinir Ağ Yöntemiyle modellenmiştir. HYSA modeli ile birlikte istatiksel indisler hesaplanmış ve model performansı kontrol edilmiştir. Sonuç olarak, model çıktıları ve istatiksel değerler incelendiğinde HYSA yapısının ozon konsantrasyonu modellemelerinde kullanılabileceği görülmüştür.
Anahtar Kelimeler
Kaynakça
- Eryılmaz, E., İstanbul’da Gece Ozonu, Yüksek
- Lisans Tezi İstanbul Teknik Üniversitesi Fen
- Bilimleri Enstitüsü, 2001.
- Tecer, L., İstanbul Kenti Fotokimyasal Smog
- Mekanizmasının Modellenmesi Doktora Tezi,
- Cumhuriyet Üniversitesi, 2000.
- Tirabassi, T., Pelliccioni, A. ve Garazzo, C.,
- “Coupling of Neural Network and Dispersion
- Models: a Novel Methodology for Air Pollution
- Models”, Int. J. Environment and Pollution,
- Cilt 20, No.1-6, 136-146, 2003.
- Wahab-Abdul, S.A. ve Al-Alawi, S.M.,
- “Assessment and Prediction of Trophospheric
- Ozone Concentration Levels Using Artificial
- Neural Networks”, Environmental Modeling &
- Software, Cilt 17, pp 219-228, 2002.
- Gardner, M.W., Dorling S.R., “Statistical Surface
- Ozone Models; an Improved Methodology to
- account for Nonlinear Behavior” Atmospheric
- Environment, Cilt 34, 21-34, 2000.
- Spellman G., “An Application of Artificial
- Neural Networks to the Prediction of Surface
- ozone Concentrations in the United Kingdom”,
- Applied Geography, Cilt 19, 123-136, 1999.
- Comrie A. C., “Comparing Neural Networks and
- Regression Model for Ozone Forecasting”,
- Journal of Air and Waste Manegement
- Association Cilt 47, 653-663, 1997.
- Jorquera H., Ricardo P.,Cipriano A., Espejo A.,
- Letelier M.V., and Acuna G., “Forecasting Ozone Daily Maximum Levels At Santiago, Chile”,
- Atmospheric Environment, Cilt. 32, 1267-1271,
- -
- Elkamel A., Wahab-Abdul S.A., Bouhamra W.,
- Alper E., “Measurement and Prediction of Ozone
- Levels Around a Heavly Industrialized Area; A
- Neural Network Approach”, Advanced in
- Environmental Reserch, Cilt 5,.47-59, 2001.
- Ruiz –Suarez J.C., Mayora-Ibarra O.A., Torres-
- Jimenes J. ve Ruiz –Suarez L.G., “Short Term
- Ozone Forecasting by Artificial Neural
- Networks”, Advances in Engineering Software,
- Cilt 23, 143-149, 1995.
- Chua L.O., Yang L.,. “Cellular Neural Networks”
- Application, IEEE Transactions on Circuits
- and Systems Cilt 35 (10), 1273-1290, 1988.
- Şahin U., Uçan O.N., Tolluoğlu O., ve Bayat C.,
- “İstanbul’un Hava Kirliliğinin Hücresel Yapay
- Sinir Ağ ile Modellenmesi”, TAINN’04 Turkish
- Symposium on Artificial Intelligence and
- Neural Networks.,2004 Izmir, Turkey
- Albora, A.M., Ucan, O.N., Ozmen, A.,ve Ozkan,
- T. “Separation of Bouguer Anomaly Map Using
- Cellular Neural Network”, Journal of Applied
- Geophysics Cilt 46, 129-142, 2001.
- Cimagalli, V. “Cellular Neural Networks A
- Review”, Proceedings of Sixth Italian
- Workshop on Parallel Architectures and
- Neural Networks, Vietri Sul Mare, May 12-14,
- , Italy
- Özcan H.K, Şahin Ü, Bayat C., Uçan O.N
- “İstanbul Şehir Atmosferindeki Troposferik Ozon
- (O3) Kirliliğinin Yapay Zeka İle Modellenmesi”,
- HİTEK’05 Havacılıkta İleri Teknolojiler
- Sempozyumu, Hava Harb Okulu, İstanbul, 2005.
Yıl 2006,
Cilt: 21 Sayı: 2, 239 - 245, 01.03.2013
Öz
In the recent years, formation of photochemical smog is common in metropolitan areas ozone is the most
important pollution which causes photochemical smog. So, many studies focus on the air quality modeling
accounted ozone and ozone precursors. In this paper, we have applied Cellular Neural Network for future
prediction of ozone concentration in the European parts of Istanbul. We have used various real data parameters
observed in 6 different air pollution and 8 meteorological parameters. As a result, CNN model results represent
the seasonal increment and decrement of observed Ozone and CNN can be considered as a compromising
approach in ozone prediction modeling.
Anahtar Kelimeler
Kaynakça
- Eryılmaz, E., İstanbul’da Gece Ozonu, Yüksek
- Lisans Tezi İstanbul Teknik Üniversitesi Fen
- Bilimleri Enstitüsü, 2001.
- Tecer, L., İstanbul Kenti Fotokimyasal Smog
- Mekanizmasının Modellenmesi Doktora Tezi,
- Cumhuriyet Üniversitesi, 2000.
- Tirabassi, T., Pelliccioni, A. ve Garazzo, C.,
- “Coupling of Neural Network and Dispersion
- Models: a Novel Methodology for Air Pollution
- Models”, Int. J. Environment and Pollution,
- Cilt 20, No.1-6, 136-146, 2003.
- Wahab-Abdul, S.A. ve Al-Alawi, S.M.,
- “Assessment and Prediction of Trophospheric
- Ozone Concentration Levels Using Artificial
- Neural Networks”, Environmental Modeling &
- Software, Cilt 17, pp 219-228, 2002.
- Gardner, M.W., Dorling S.R., “Statistical Surface
- Ozone Models; an Improved Methodology to
- account for Nonlinear Behavior” Atmospheric
- Environment, Cilt 34, 21-34, 2000.
- Spellman G., “An Application of Artificial
- Neural Networks to the Prediction of Surface
- ozone Concentrations in the United Kingdom”,
- Applied Geography, Cilt 19, 123-136, 1999.
- Comrie A. C., “Comparing Neural Networks and
- Regression Model for Ozone Forecasting”,
- Journal of Air and Waste Manegement
- Association Cilt 47, 653-663, 1997.
- Jorquera H., Ricardo P.,Cipriano A., Espejo A.,
- Letelier M.V., and Acuna G., “Forecasting Ozone Daily Maximum Levels At Santiago, Chile”,
- Atmospheric Environment, Cilt. 32, 1267-1271,
- -
- Elkamel A., Wahab-Abdul S.A., Bouhamra W.,
- Alper E., “Measurement and Prediction of Ozone
- Levels Around a Heavly Industrialized Area; A
- Neural Network Approach”, Advanced in
- Environmental Reserch, Cilt 5,.47-59, 2001.
- Ruiz –Suarez J.C., Mayora-Ibarra O.A., Torres-
- Jimenes J. ve Ruiz –Suarez L.G., “Short Term
- Ozone Forecasting by Artificial Neural
- Networks”, Advances in Engineering Software,
- Cilt 23, 143-149, 1995.
- Chua L.O., Yang L.,. “Cellular Neural Networks”
- Application, IEEE Transactions on Circuits
- and Systems Cilt 35 (10), 1273-1290, 1988.
- Şahin U., Uçan O.N., Tolluoğlu O., ve Bayat C.,
- “İstanbul’un Hava Kirliliğinin Hücresel Yapay
- Sinir Ağ ile Modellenmesi”, TAINN’04 Turkish
- Symposium on Artificial Intelligence and
- Neural Networks.,2004 Izmir, Turkey
- Albora, A.M., Ucan, O.N., Ozmen, A.,ve Ozkan,
- T. “Separation of Bouguer Anomaly Map Using
- Cellular Neural Network”, Journal of Applied
- Geophysics Cilt 46, 129-142, 2001.
- Cimagalli, V. “Cellular Neural Networks A
- Review”, Proceedings of Sixth Italian
- Workshop on Parallel Architectures and
- Neural Networks, Vietri Sul Mare, May 12-14,
- , Italy
- Özcan H.K, Şahin Ü, Bayat C., Uçan O.N
- “İstanbul Şehir Atmosferindeki Troposferik Ozon
- (O3) Kirliliğinin Yapay Zeka İle Modellenmesi”,
- HİTEK’05 Havacılıkta İleri Teknolojiler
- Sempozyumu, Hava Harb Okulu, İstanbul, 2005.
Toplam 64 adet kaynakça vardır.
Ayrıntılar
| Birincil Dil | Türkçe |
|---|---|
| Konular | Mimarlık |
| Bölüm | Makaleler |
| Yazarlar | |
| Yayımlanma Tarihi | 1 Mart 2013 |
| Gönderilme Tarihi | 3 Haziran 2014 |
| Yayımlandığı Sayı | Yıl 2006 Cilt: 21 Sayı: 2 |