DATA GENERATION FOR MURAT RIVER WITH ARTIFICIAL NEURAL NETWORKS


Albostan A., Barutçu B. , Önöz B.

5th IASME/WSEAS International Conference on Water Resources, Hydraulics and Hydrology/4th IASME/WSEAS International Conference on Geology and Seismology, Cambridge, Canada, 23 - 25 February 2010, pp.73-77 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Cambridge
  • Country: Canada
  • Page Numbers: pp.73-77

Abstract

Due to the cause of global warming threat and climate change, effective and efficient use of natural resources has become a great significance to ensure sustainability. Hence, the Water resources data need correct measurement, analysis, and reliable estimates. In this study, the daily-flow rate data of observation stations located on Firat River were grouped in three and a data of one station were generated by using other two. In data generation both Artificial Neural Network and Multi Linear Regression methods were used. Both methods results were compared with each other and tested with real data.