Araştırma Makalesi

DATA MINING PROCESS FOR RIVER SUSPENDED SEDIMENT ESTIMATION

Cilt: 8 Sayı: 3 1 Aralık 2016
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DATA MINING PROCESS FOR RIVER SUSPENDED SEDIMENT ESTIMATION

Öz

The accurate estimation of the amount of suspended sediment of rivers is important in water resources engineering because sediment in rivers can also shorten the lifespan of dams and reservoirs. For this purpose, the models are developed to estimate suspended sediment of Kızılırmak River using the data mining process. The river flow values are used as input parameter by developing sediment models. The most appropriate model is obtained by the M5’Rules algorithm. The determination coefficient of the model is obtained as 0.66 and it is observed that the data mining process can be used to estimate suspended sediment of rivers in hydrology field.

Anahtar Kelimeler

Kaynakça

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  5. Hall , M.J., Minns, A.W., Ashrafuzzaman, A.K.M. (2002). The application of data mining techniques for the regionalisation of hydrological variables. Hydrology and Earth System Sciences. vol. 6(4), pp. 685-694.
  6. Hall, M., Holmes, G., Frank, E. (1999). Generating Rule Sets from Model Trees. Proceedings of the Twelfth Australian Joint Conference on Artificial Intelligence. pp. 1-12., Sydney, Australia .
  7. Heng, S. and Suetsugi, T. (2013). Using Artificial Neural Network to Estimate Sediment Load in Ungauged Catchments of the Tonle Sap River Basin, Cambodia. Journal of Water Resource and Protection, vol. 5(2), pp. 111-123.
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Ayrıntılar

Birincil Dil

İngilizce

Konular

İnşaat Mühendisliği

Bölüm

Araştırma Makalesi

Yazarlar

Tahsin Baykal Bu kişi benim

Yayımlanma Tarihi

1 Aralık 2016

Gönderilme Tarihi

25 Temmuz 2016

Kabul Tarihi

2 Aralık 2016

Yayımlandığı Sayı

Yıl 2016 Cilt: 8 Sayı: 3

Kaynak Göster

APA
Terzi, Ö., & Baykal, T. (2016). DATA MINING PROCESS FOR RIVER SUSPENDED SEDIMENT ESTIMATION. Uluslararası Teknolojik Bilimler Dergisi, 8(3), 19-26. https://izlik.org/JA85FE65GX
AMA
1.Terzi Ö, Baykal T. DATA MINING PROCESS FOR RIVER SUSPENDED SEDIMENT ESTIMATION. UTBD. 2016;8(3):19-26. https://izlik.org/JA85FE65GX
Chicago
Terzi, Özlem, ve Tahsin Baykal. 2016. “DATA MINING PROCESS FOR RIVER SUSPENDED SEDIMENT ESTIMATION”. Uluslararası Teknolojik Bilimler Dergisi 8 (3): 19-26. https://izlik.org/JA85FE65GX.
EndNote
Terzi Ö, Baykal T (01 Aralık 2016) DATA MINING PROCESS FOR RIVER SUSPENDED SEDIMENT ESTIMATION. Uluslararası Teknolojik Bilimler Dergisi 8 3 19–26.
IEEE
[1]Ö. Terzi ve T. Baykal, “DATA MINING PROCESS FOR RIVER SUSPENDED SEDIMENT ESTIMATION”, UTBD, c. 8, sy 3, ss. 19–26, Ara. 2016, [çevrimiçi]. Erişim adresi: https://izlik.org/JA85FE65GX
ISNAD
Terzi, Özlem - Baykal, Tahsin. “DATA MINING PROCESS FOR RIVER SUSPENDED SEDIMENT ESTIMATION”. Uluslararası Teknolojik Bilimler Dergisi 8/3 (01 Aralık 2016): 19-26. https://izlik.org/JA85FE65GX.
JAMA
1.Terzi Ö, Baykal T. DATA MINING PROCESS FOR RIVER SUSPENDED SEDIMENT ESTIMATION. UTBD. 2016;8:19–26.
MLA
Terzi, Özlem, ve Tahsin Baykal. “DATA MINING PROCESS FOR RIVER SUSPENDED SEDIMENT ESTIMATION”. Uluslararası Teknolojik Bilimler Dergisi, c. 8, sy 3, Aralık 2016, ss. 19-26, https://izlik.org/JA85FE65GX.
Vancouver
1.Özlem Terzi, Tahsin Baykal. DATA MINING PROCESS FOR RIVER SUSPENDED SEDIMENT ESTIMATION. UTBD [Internet]. 01 Aralık 2016;8(3):19-26. Erişim adresi: https://izlik.org/JA85FE65GX

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