| The problem of population aging in our country is becoming more and more serious.Because of the aging of the population structure,various social problems begin to appear.As the proportion of the aged population continues to increase,the proportion of young and middle-aged labor force continues to decline,which has an impact on the development of the state and society.What's more,China is now facing the unfavorable situation of "not getting rich before it grows old".As the aging population increases,there is no perfect and adequate policy system to support the family burden and social burden.Thus,the importance of accurate prediction of the aging population is highlighted.Nowadays,the methods of population prediction can be varied,and each method has its own advantages and disadvantages.This paper will study the grey prediction model,and use the model and the optimized model to predict the aging population.The specific research is divided into three parts:Firstly,this paper introduces the related theories of grey model,and gives the original grey forecasting model,and gives the steps of forecasting.In addition,several test methods for prediction accuracy are given in this paper.The accuracy of the model is tested and the optimization direction is put forward.Second,according to the previous research on the original model,this paper will optimize the model from several directions.The improvement of smoothness is given in terms of sequence smoothness,and the improvement of background value is given in the direction of model background value.How to use grey combination prediction model to improve prediction accuracy is given.Third,this paper will model the number of aged people from 2005 to 2014.The data are tested by the original model and the improved model respectively,and the prediction accuracy of each model is compared.The optimization method with the highest precision is selected,and the prediction value of the aged population in the following ten years is given. |
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