Forecasting Spatial Migration Tendency with FGM(1,1) and Hidden Markov Model

Population spatial migration tendency forecasting is very important for the research of spatial demography. Traditional approaches are too complex to be used for time series prediction. This paper presents a method combinating Hidden Markov Model (HMM) and Fourier Series Grey Model (FGM) based on Grey Model (GM) to predict the trend of Jiangsu Province’s migration in China. There are three parts of forecast. The first one is to build GM from a series of coordinate data, the second uses the Fourier series to refine the residuals produced by the mentioned model and the third uses HMM to refine the residuals of FGM .It is evident that the proposed approach gets the better result performance in studying the population migration. Satisfactory results have been obtained, which improve HMM-FGM reached when only GM was used for the population spatial migration tendency forecasting.