Dissolved oxygen estimation using artificial neural network for water quality control
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Dosyalar
Tarih
2006
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Parlar Scientific Publications (P S P)
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Dissolved oxygen (DO) is one of the key parameters when analyzing river water quality. Correct estimation of DO being carried by a river is very important for water quality control. DO is affected by lots of variables such as decomposition, nitrification, reaeration, sedimentation, photosynthesis, water discharge and temperature for that reason it is hard to solve such a complex problem. The methods available in the literature for DO estimation are complicated, time consuming and necessitate numbersome parameter estimation procedures. Artificial Neural Networks (ANNs) are simply mathematical representations of the functioning of the human brain. This paper examines the potential of ANN in estimating the DO from limited data (NO2-N, NO3-N, BOD, water discharge and temperature). This study employed feed forward (FF) type ANN for computing monthly values of DO. The results of the study clearly demonstrate that the ANN results are very close to the observed values of DO.
Açıklama
13th International Symposium on Environmental Pollution and Its Impact on Life in the Mediterranean Region -- OCT 08-12, 2005 -- Thessaloniki, GREECE
Anahtar Kelimeler
Artificial Neural Network, Dissolved Oxygen, Water Quality
Kaynak
Fresenius Environmental Bulletin
WoS Q Değeri
Q4
Scopus Q Değeri
N/A
Cilt
15
Sayı
9A
