DATA MINING PROCESS FOR RIVER SUSPENDED SEDIMENT ESTIMATION

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Uluslararası Teknolojik Bilimler Dergisi
Volume:8 Issue:3
DATA MINING PROCESS FOR RIVER SUSPENDED SEDIMENT ESTIMATION

DATA MINING PROCESS FOR RIVER SUSPENDED SEDIMENT ESTIMATION

Authors : Özlem Terzi, Tahsin Baykal

Pages : 19-26

View : 100 | Download : 8

Publication Date : 2016-12-01

Article Type : Research Paper

Abstract :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.
Keywords : sediment, data mining process, M5`Rules, Kızılırmak River

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