The Population system is a dynamical system.The trend of a Population willaffect the development of the soeiety and its economy. The age strueture is one of themost important Indexes in Population researeh.The foreeast of agrstructure plays animportant role in making Population Polieies.The paper using Heilongjiang provincepopulation quantity and structure as the research object,builting a grey model andpopulation development equation to forecast the future of Heilongjiang provincepopulation and the structure, which will help the government formulate effectivemacroeconomic policies on population and development.This paper analyzes that the function transformation of original data sequence canbe improve the prediction accuracy of grey model, but the function transformationshould be integrated into a whole lot of aspects, first is to improve the smooth of theoriginal data, the second is to adjust the ratio of compression, but also we must ensurereduction error will not be enlarged, these three factors can be used as a datatransformation criterion, at the same time, based on these data transformation rules, thispaper gives a new function transformation method, combined with Heilongjiang censusdata, verified the effectiveness of the function transformation, it proved that functiontransform method proposed in this paper can expand the applicability of greyforecasting model, but also can improve the prediction accuracy.A discrete model of population development equation is build in this paper, basedon combination of fertility rate model and subsection mortality model, iteration to thepopulation development equation, prediction and analysis of population structure ontrends in Heilongjiang Province, compared with the traditional model, the combinationof fertility rate model and subsection mortality model fit well, improved the predictionaccuracy, and they are dffective tools and models to solve birth and death problem, atthe same time with the demographic data of Heilongjiang Province in2010as theoriginal data, the effectiveness of the model was verified, Finally, according to thedevelopment trend of index of population prediction shows the future of Heilongjiangprovince, given some reasonable proposals. |