Based on ODE and ARIMA Modeling for the population of China

¹ School of Mathematics and Statistics, Hainan Normal University,Haikou, China

² School of Mathematics and Statistics, Hainan Normal University,Haikou, China

Abstract

The economic data usually can be also composed into a deterministic part and a random part. We establish ordinary differential equations (ODE) model for the deterministic part from a purely mathematical point of view, via the prin-ciple of integral and difference, establishing ()ARIMApdq,, model for the random part, to combine the two estab-lished models to predict and control the original series, then we apply the method to study the population of China from 1978 to 2007, establishing the corresponding mathematical model, to obtain the forecast data of the population of China in 2008(1.3879503 billion), finally we make further stability analysis.

KeywordsNatural AssetFinancial ValueNeural Network

Zhu Minhui. Fitting Gompertz Model and Logistic Model.J. Mathematics in Practice and Theory,2003;2:705-709.
Peter J.Brockwell et al. Time series: theory and methods (2nd edn).China Higher Education Press Beijing and Springer-Verlag Berlin Heidelberg:Beijing,2001;75.
Yi Danhui.Data analysis and Eviews application. China Statistics Press:Beijing,2002;66-70.
Zhang Shiying.The financial time series analysis. Tsinghua University Press:Beijing,2008;90-93.
Philip Hans Franses.Time Series Models for Business and Economic Forecasting[M].Beijing: Chinese People’s University Press.2002.
http//www.cpachn.org.cn/chinese/Teaching/Information.asp?,2009-05-02.
Tongji University Department of Applied Mathematics. Advanced Mathematics (5th edn), Beijing: Higher Education Press.2004.

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Based on ODE and ARIMA Modeling for the population of China

Abstract

References (7)