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Investigating the effect of previous time on modeling stage–discharge curve at hydrometric stations using GEP and NN models
The present study aims to apply different methods to investigate effect of previous time of discharge and stage on modeling stage–discharge curve at two hydrometric stations (Faraman and Qorbaghestan stations of Qara Sou River) using measured data-set through the artificial networks (ANNs) and Genetic Expression Programming (GEP) techniques. Subsequently, stage and discharge data of several consecutive water years are applied as models input–output variables. The obtained results indicate that applied machine learning techniques (GEP and ANNs) have reliable performance in modeling stage–discharge curve and can be used instead of other methods. As well as previous time discharge and stage have positive influence on modeling stage–discharge curve.
Investigating the effect of previous time on modeling stage–discharge curve at hydrometric stations using GEP and NN models
The present study aims to apply different methods to investigate effect of previous time of discharge and stage on modeling stage–discharge curve at two hydrometric stations (Faraman and Qorbaghestan stations of Qara Sou River) using measured data-set through the artificial networks (ANNs) and Genetic Expression Programming (GEP) techniques. Subsequently, stage and discharge data of several consecutive water years are applied as models input–output variables. The obtained results indicate that applied machine learning techniques (GEP and ANNs) have reliable performance in modeling stage–discharge curve and can be used instead of other methods. As well as previous time discharge and stage have positive influence on modeling stage–discharge curve.
Investigating the effect of previous time on modeling stage–discharge curve at hydrometric stations using GEP and NN models
Harasami, Farshad (author) / Akhgar, Samira (author) / Javan, Mitra (author) / Shiri, Jalal (author)
ISH Journal of Hydraulic Engineering ; 23 ; 293-300
2017-09-02
8 pages
Article (Journal)
Electronic Resource
English
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