AERATION EFFICIENCY ESTIMATION IN STEPPED CASCADE AERATORSUSING NEURAL NETWORK APPROACH

Cilt: 3 Sayı: 2 1 Mart 2008
  • Ahmet Baylar
Engineering Sciences Kapak
Engineering Sciences
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AERATION EFFICIENCY ESTIMATION IN STEPPED CASCADE AERATORSUSING NEURAL NETWORK APPROACH

Öz

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.

Anahtar Kelimeler

Ayrıntılar

Birincil Dil

Türkçe

Konular

-

Bölüm

-

Yazarlar

Ahmet Baylar Bu kişi benim

Yayımlanma Tarihi

1 Mart 2008

Gönderilme Tarihi

29 Ağustos 2014

Kabul Tarihi

-

Yayımlandığı Sayı

Yıl 2008 Cilt: 3 Sayı: 2

DOI

https://doi.org/10.12739/nwsaes.v3i2.5000067196

IZ

https://izlik.org/JA66EW48NL

Kaynak Göster

RIS / Bibtex
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
1.Baylar A. AERATION EFFICIENCY ESTIMATION IN STEPPED CASCADE AERATORSUSING NEURAL NETWORK APPROACH. Engineering Sciences. 2008;3(2):360-371. doi:10.12739/nwsaes.v3i2.5000067196
Chicago
Baylar, Ahmet. 2008. “AERATION EFFICIENCY ESTIMATION IN STEPPED CASCADE AERATORSUSING NEURAL NETWORK APPROACH”. Engineering Sciences 3 (2): 360-71. https://doi.org/10.12739/nwsaes.v3i2.5000067196.
EndNote
Baylar A (01 Mart 2008) AERATION EFFICIENCY ESTIMATION IN STEPPED CASCADE AERATORSUSING NEURAL NETWORK APPROACH. Engineering Sciences 3 2 360–371.
IEEE
[1]A. Baylar, “AERATION EFFICIENCY ESTIMATION IN STEPPED CASCADE AERATORSUSING NEURAL NETWORK APPROACH”, Engineering Sciences, c. 3, sy 2, ss. 360–371, Mar. 2008, doi: 10.12739/nwsaes.v3i2.5000067196.
ISNAD
Baylar, Ahmet. “AERATION EFFICIENCY ESTIMATION IN STEPPED CASCADE AERATORSUSING NEURAL NETWORK APPROACH”. Engineering Sciences 3/2 (01 Mart 2008): 360-371. https://doi.org/10.12739/nwsaes.v3i2.5000067196.
JAMA
1.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, c. 3, sy 2, Mart 2008, ss. 360-71, doi:10.12739/nwsaes.v3i2.5000067196.
Vancouver
1.Ahmet Baylar. AERATION EFFICIENCY ESTIMATION IN STEPPED CASCADE AERATORSUSING NEURAL NETWORK APPROACH. Engineering Sciences. 01 Mart 2008;3(2):360-71. doi:10.12739/nwsaes.v3i2.5000067196