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Khabur River Flow Modeling using Artificial Neural Networks | ||
| Al-Rafidain Engineering Journal (AREJ) | ||
| Article 6, Volume 13, Issue 2, 2005, Pages 33-42 PDF (0 K) | ||
| DOI: 10.33899/rengj.2005.45629 | ||
| Authors | ||
| Jowhar R. Muhamad; Jwan N. Hassan | ||
| Abstract | ||
| Abstract: Modeling a hydrologic time series has been one of the most complicated tasks owing to the wide range of data, the uncertainties in the parameters influencing the time series and also due to the non availability of adequate data. Recently, Artificial Neural Networks (ANNs) have become quite popular in time series forecasting in various fields. This paper demonstrates the use of ANNs to forecast Khabur monthly river flows for flow data from January 1958 to December 1975. Using the feed forward network. The network is trained using the lagged or delayed variables from SARIMA model as an input variables for the network. ANN model for mouthy flow gives better result in comparison with Traditional ANN models and SARIMA model. | ||
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