A. Danandehmehr; M.R. Majdzadeh Tabatabaei
Abstract
Abstract
Accurate prediction of river flow is one of the most important factors in surface water recourses management especially during floods and drought periods. In fact deriving a proper method for flow forecasting is an important challenge in water resources management and engineering. Although, ...
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Abstract
Accurate prediction of river flow is one of the most important factors in surface water recourses management especially during floods and drought periods. In fact deriving a proper method for flow forecasting is an important challenge in water resources management and engineering. Although, during recent decades, some black box models based on artificial neural networks (ANN), have been developed to overcome this problem and the accuracy privilege to common statistical methods (such as auto regression and moving average time series method) have been shown. However these types of models are implicit and complex in proper network design and can not be simply used by other investigators. In this research the genetic programming (GP) model has been developed as an explicit method for river flow prediction and has been used for investigation the effect of daily discharge trend in Absardeh river flow forecasting. The results have been compared with artificial neural network technique. The results indicated that the proposed GP method performed quite well compared to artificial neural network method and is applicable for river flow prediction.
Keywords: Daily discharge, Flow prediction, Genetic programming
