AERATION EFFICIENCY ESTIMATION IN STEPPED CASCADE AERATORSUSING NEURAL NETWORK APPROACH

Volume: 3 Number: 2 March 1, 2008
  • Ahmet Baylar
Engineering Sciences Cover
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

Details

Primary Language

Turkish

Subjects

-

Journal Section

-

Authors

Ahmet Baylar This is me

Publication Date

March 1, 2008

Submission Date

August 29, 2014

Acceptance Date

-

Published in Issue

Year 2008 Volume: 3 Number: 2

DOI

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

IZ

https://izlik.org/JA66EW48NL

Cite

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 (March 1, 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, vol. 3, no. 2, pp. 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 (March 1, 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, vol. 3, no. 2, Mar. 2008, pp. 360-71, doi:10.12739/nwsaes.v3i2.5000067196.
Vancouver
1.Ahmet Baylar. AERATION EFFICIENCY ESTIMATION IN STEPPED CASCADE AERATORSUSING NEURAL NETWORK APPROACH. Engineering Sciences. 2008 Mar. 1;3(2):360-71. doi:10.12739/nwsaes.v3i2.5000067196