Determination of the number of clusters used in fuzzy inference systems by means of K-means and modeling of dam volume: Kestel dam example


Creative Commons License

KÜÇÜKERDEM ÖZTÜRK T. S. , KİLİT M., SAPLIOĞLU K.

PAMUKKALE UNIVERSITY JOURNAL OF ENGINEERING SCIENCES-PAMUKKALE UNIVERSITESI MUHENDISLIK BILIMLERI DERGISI, cilt.25, ss.962-967, 2019 (ESCI İndekslerine Giren Dergi) identifier

  • Cilt numarası: 25 Konu: 8
  • Basım Tarihi: 2019
  • Doi Numarası: 10.5505/pajes.2019.99223
  • Dergi Adı: PAMUKKALE UNIVERSITY JOURNAL OF ENGINEERING SCIENCES-PAMUKKALE UNIVERSITESI MUHENDISLIK BILIMLERI DERGISI
  • Sayfa Sayıları: ss.962-967

Özet

Correct planning of water resources is important for the efficient use of rapidly decreasing water resources in the future. Flow modeling and flow estimations in the planning of water resource are the basis of studies. In this study, it is aimed to estimate monthly volumes by using ANFIS model based on the data of 1986-2008 for Sandikli Kestel dam. In the system, the volume of the previous months, the volume of the incoming and outgoing volumes and the amount of evaporation were used as input variables. In ANFIS method, the number of clusters used for the inputs was obtained by the method of K-means. Different clusters formed by K-averages were modeled in ANFIS and the results were compared. The optimal number of clusters for each input value is determined. Models have been established in this way. As a result, it has been found that the models made according to the optimal number of clusters yield results with lower error percentage compared to randomly generated models.