DocumentCode
175959
Title
Analysis of population controllability and prediction of population structure based on constraint system
Author
Yue Xiao-ning ; Meng Zhao-jia ; Xie Feng-dan
Author_Institution
Coll. of Normal, Shenyang Univ., Shenyang, China
fYear
2014
fDate
May 31 2014-June 2 2014
Firstpage
1672
Lastpage
1676
Abstract
It is established that population structure prediction time-varying restriction system model, and its controllability of the system is analyzed through grey system theory and control theory. Based on Liapunov central limit theorem, the conclusion that child-bearing age of women is subject to the normal distribution is obtained, and the density function of fertility age is given. Fertility restricted function is introduced, and we define population migration quantity as control variable, and state feedback gain matrix is established by fertility restricted function, on the basis of which, the discrete time-varying population structure restriction system is established, at the same time its controllability is analyzed by the fertility restriction function and population structure is predicted in a closed region. Finally, error analysis is made through the model, and accuracy and dependability of the model are proved.
Keywords
demography; error analysis; forecasting theory; grey systems; matrix algebra; Lyapunov central limit theorem; constraint system; control theory; discrete time-varying population structure restriction system; error analysis; fertility age density function; fertility restriction function; grey system theory; population controllability analysis; population migration quantity; population structure prediction; state feedback gain matrix; Analytical models; Controllability; Educational institutions; Pediatrics; Predictive models; Sociology; Statistics; Controllability; Fertility rate; Grey constraint system; Population structure; Prediction;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (2014 CCDC), The 26th Chinese
Conference_Location
Changsha
Print_ISBN
978-1-4799-3707-3
Type
conf
DOI
10.1109/CCDC.2014.6852437
Filename
6852437
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