TY - JOUR T1 - Streamflow Forecasting Using Neuro-Fuzzy and Time Series Methods TT - پیش‌بینی دبی رودخانه با استفاده از روش‌های نوروفازی و مدل‌های سری‌های زمانی JF - ijwmse JO - ijwmse VL - 2 IS - 5 UR - http://jwmsei.ir/article-1-90-en.html Y1 - 2009 SP - 21 EP - 30 KW - Time Serie KW - ANFIS KW - River Discharge KW - Artifitial Neural Network and Taleghan River. N2 - Simulation of river flow in order to understand the river yield in the future is one of the important andpractical issues in water resource management. In this study, monthly discharge of Taleghan river in Glinakstations at one step proceeding were forecasted using Artificial Intelligent (Artificial Neural Network MLP,ANFIS with Grid Partition and Subtractive Clustering) and time series methods. Two inputs including rawdischarge data and de-seasonalised discharge data were used for different models. For time series models,ARIMA (3,0,0)(0,1,1) were selected as suitable model. The optimum structure in Artificial Intelligencemethod after pre-processing was determined using input and output data based on trial and error, and then,using the optimum structure, the streamflow discharge was forecasted. After the output of each singlemodel was obtained, the structure of hybrid models were determined. The results showed hybrid methods3 and 2 have the best application and time series model has better results than Artificial Intelligent methods. M3 ER -