Leila Naghipour

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This research aims to model Total Dissolved Solid (TDS) values at the Simineh River in northwest Iran by application of Artificial Neural Networks (ANNs) to evaluate existing water quality conditions and also to predict future conditions in this river. The input parameters of the ANNs model are Calcium (Ca), Chloride (Cl), Magnesium (Mg), Sodium (Na),(More)
Recorded time series of relative humidity (RH) are modeled by using genetic expression programming (GEP) and artificial neural networks (ANNs) models. The data are noisy and contain missing datapoints. RH is modeled as a function of three meteorological variables: temperature, wind speed, and pressure. Various model structures of both of these models are(More)
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