TY - JOUR T1 - Comparison of Gene Expression Programming (GEP) and Parametric and Non-parametric Regression Methods in the Prediction of the Mean Daily Discharge of Karun River (A case Study: Mollasani Hydrometric Station) TT - مقایسه روش‌های برنامه‌ریزی بیان ژن و رگرسیون‌های پارامتریک و ناپارامتریک در پیش‌بینی دبی میانگین روزانه رودخانه کارون (مطالعه موردی: ایستگاه هیدرومتری ملاثانی) JF - JSTNAR JO - JSTNAR VL - 25 IS - 1 UR - http://jstnar.iut.ac.ir/article-1-3999-en.html Y1 - 2021 SP - 43 EP - 62 KW - River discharge KW - Gene expression programming KW - Linear and nonlinear regression KW - K- nearest neighbor KW - Karun. N2 - Nowadays, the prediction of river discharge is one of the important issues in hydrology and water resources; the results of daily river discharge pattern could be used in the management of water resources and hydraulic structures and flood prediction. In this research, Gene Expression Programming (GEP), parametric Linear Regression (LR), parametric Nonlinear Regression (NLR) and non-parametric K- Nearest Neighbor (K-NN) were used to predict the average daily discharge of Karun River in Mollasani hydrometric station for the statistical period of 1967-2017. Different combinations of the recorded data were used as the input pattern to predict the mean daily river discharge. The obtained esults indicated that GEP, with R2= 0.827, RMSE= 59.45 and MAE= 26.64, had a better performance, as compared to LR, NLR and K-NN methods, at the validation stage for daily Karun River discharge prediction with 5-day lag, at the Mollasani station. Also, the performance of the models in the maximum discharge prediction showed that all models underestimated the flow discharge in most cases. M3 10.47176/jwss.25.1.1012 ER -