Abstract for: An Adaptive Statistical Data Processing Algorithm Applied to SD Modeling of Iran’s Demographic Transition

There are different official estimations about current and future growth rate of Iran’s population. Inadequacy and unreliability of data in addition to usage of unsuitable forecasting methods are the main reasons for existence of this variety. To have accurate estimates for year on year growth rate, in this research, a population system dynamics model is implemented. To run the model, total fertility rate and other needful fertility parameters are calculated by processing raw data. In the next step and to resolve the statistical inconsistencies in census data which have been revealed by calculation of survival fractions and death rates, an appropriate adaptive process is proposed and applied to modify the parameters. The result of applying model shows that the next ten-year average growth rate will be about 1.9. Finally, simulation results of three possible scenarios on the fertility factor are obtained that warns on exceeding of population over 100m by 2020.