Gross Domestic Product (GDP) is one of the most important economic attributes among private and government sectors. Long and short term forecasts of such variable can be a basis for selection of appropriate fiscal policies and investments. It is apparent that the more difference between forecasts and reality exists, the more inefficient policies can become. Since economic activities are mostly seasonal and have seasonal behaviors, analyzing them using seasonal data can be more efficient and accurate. Of course, utilizing high frequency data has been an active field of research, recently. Recent progresses in quantitative models, specifically in the field of forecasting, has made basic changes in these models so that better results with less deviations can be achieved. In this thesis, it is tried to propose a short term forecasting system to forecast seasonal nominal and seasonal real GDP. We hope to take a small part in progression of our national economy growth. There are several forecasting methods which can be grouped into justify; LINE-HEIGHT: normal; TEXT-INDENT: 18pt; MARGIN: 0cm 0cm 0pt" . After modeling and forecasting nominal and real seasonal GDPs, quarter-on-quarter and also year-on-year growth rates were also calculated and their related errors were computed. In order to calculate the deviations, two indexes MAPE and RMSE were implemented. It is noteworthy to mention that forecasts being done are for maximum 8 seasons on a forward basis. More accurately, the results are calculated for 1, 2, …, 8 seasons on a forward manner but 8 steps forecasts have been considered and analyzed more than the others. Computational results for forecasting quarterly nominal GDP, quarterly real GDP, quarter-on-quarter growth rate, and year-on-year growth rate entirely demonstrate that considering MAPE index, ANFIS method on comparison to SARIMA is much more superior. Minimum improvements in above four states are: 33% in 7 steps of forecasting, 59% in 8 steps of forecasting, 48% in 7 steps of forecasting, and 62% in 8 steps of forecasting.
