M5 model tree application in daily river flow forecasting in Sohu Stream, Turkey

Sattari M. T., Pal M., APAYDIN H., Ozturk F.

WATER RESOURCES, vol.40, no.3, pp.233-242, 2013 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 40 Issue: 3
  • Publication Date: 2013
  • Doi Number: 10.1134/s0097807813030123
  • Journal Name: WATER RESOURCES
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.233-242
  • Keywords: M5 model tree, support vector machine, Daily river flow, Sohu, Turkey, NEURAL-NETWORKS, MACHINE, PERFORMANCE
  • Ankara University Affiliated: Yes

Abstract

This study investigate the potential of M5 model tree in predicting daily stream flows in Sohu river located within the municipal borders of Ankara, Turkey. The results of the M5 model tree was compared with support vector machines. Both modelling approaches were used to forecast up to 7-day ahead stream flow. A comparison of correlation coefficient and root mean square value indicates that M5 model tree approach works equally well to the SVM for same day discharge prediction. The M5 model tree also works well up to 7-day ahead discharge forecasting in comparison of SVM with this data set. An advantage of using M5 model tree approach is the availability of simple linear models to predict the discharge as well use of less computational time.