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SİNİR AĞI YAKLAŞIMI KULLANARAK BASAMAKLI KASKAT HAVALANDIRICILARDA HAVALANDIRMA VERİMİNİN TAHMİNİ

Year 2008, Volume: 3 Issue: 2, 360 - 371, 01.03.2008

Abstract

Yüzey sularındaki oksijen konsantrasyonu suda yaşayan canlılar için olduğu kadar insani kullanım içinde su kalitesinin başlıca göstergesidir. Atmosferden oksijen transferi veya oksijen absorpsiyonunun fiziksek yöntemi, kullanılmış oksijeni tekrar kazanmak için harekete geçmektir. Bu yöntem havalandırma olarak isimlendirilir. Makro pürüzlülük yardımıyla havalandırmanın arttırılması, su arıtımında iyi bir şekilde bilinir ve bunun bir tipi havalandırma kaskatlarıdır. Basamakların makro pürüzlülüğü, akım hızını önemli bir derecede azaltır ve basamaklı kaskat boyunca akım havalanmasına yol açar. Bu makale, basamaklı kaskat havalandırıcılarda havalandırma veriminin tahmini için kullanılabilecek yapay sinir ağlarının performansını araştırmaktadır. Sonuç olarak, basamaklı kaskat havalandırıcılarda havalandırma veriminin modellenmesinde yapay sinir ağı modelinin başarılı bir şekilde kullanılabileceği görülmüştür.

AERATION EFFICIENCY ESTIMATION IN STEPPED CASCADE AERATORSUSING NEURAL NETWORK APPROACH

Year 2008, Volume: 3 Issue: 2, 360 - 371, 01.03.2008

Abstract

The oxygen concentration in surface waters is a prime indicator of the water quality for human use as well as for the aquatic biota. The physical process of oxygen transfer or oxygen absorption from the atmosphere acts to replenish the used oxygen. This process is termed re-aeration or aeration. Aeration enhancement by macro-roughness is well-known in water treatment, and one form is the aeration cascade. The macro-roughness of the steps significantly reduces flow velocities and leads to flow aeration along the stepped cascade. This paper seeks the performance of artificial neural networks (ANNs) for the estimation of aeration efficiency in stepped cascade aerators. Consequently, it is demonstrated that an ANN model could be employed successfully in modeling aeration efficiency in stepped cascade aerators.

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Details

Primary Language Turkish
Journal Section Computer Engineering
Authors

Ahmet Baylar This is me

Publication Date March 1, 2008
Published in Issue Year 2008 Volume: 3 Issue: 2

Cite

APA Baylar, A. (2008). AERATION EFFICIENCY ESTIMATION IN STEPPED CASCADE AERATORSUSING NEURAL NETWORK APPROACH. Engineering Sciences, 3(2), 360-371. https://doi.org/10.12739/nwsaes.v3i2.5000067196
AMA Baylar A. AERATION EFFICIENCY ESTIMATION IN STEPPED CASCADE AERATORSUSING NEURAL NETWORK APPROACH. Engineering Sciences. March 2008;3(2):360-371. doi:10.12739/nwsaes.v3i2.5000067196
Chicago Baylar, Ahmet. “AERATION EFFICIENCY ESTIMATION IN STEPPED CASCADE AERATORSUSING NEURAL NETWORK APPROACH”. Engineering Sciences 3, no. 2 (March 2008): 360-71. https://doi.org/10.12739/nwsaes.v3i2.5000067196.
EndNote Baylar A (March 1, 2008) AERATION EFFICIENCY ESTIMATION IN STEPPED CASCADE AERATORSUSING NEURAL NETWORK APPROACH. Engineering Sciences 3 2 360–371.
IEEE A. Baylar, “AERATION EFFICIENCY ESTIMATION IN STEPPED CASCADE AERATORSUSING NEURAL NETWORK APPROACH”, Engineering Sciences, vol. 3, no. 2, pp. 360–371, 2008, doi: 10.12739/nwsaes.v3i2.5000067196.
ISNAD Baylar, Ahmet. “AERATION EFFICIENCY ESTIMATION IN STEPPED CASCADE AERATORSUSING NEURAL NETWORK APPROACH”. Engineering Sciences 3/2 (March 2008), 360-371. https://doi.org/10.12739/nwsaes.v3i2.5000067196.
JAMA Baylar A. AERATION EFFICIENCY ESTIMATION IN STEPPED CASCADE AERATORSUSING NEURAL NETWORK APPROACH. Engineering Sciences. 2008;3:360–371.
MLA Baylar, Ahmet. “AERATION EFFICIENCY ESTIMATION IN STEPPED CASCADE AERATORSUSING NEURAL NETWORK APPROACH”. Engineering Sciences, vol. 3, no. 2, 2008, pp. 360-71, doi:10.12739/nwsaes.v3i2.5000067196.
Vancouver Baylar A. AERATION EFFICIENCY ESTIMATION IN STEPPED CASCADE AERATORSUSING NEURAL NETWORK APPROACH. Engineering Sciences. 2008;3(2):360-71.