Chaos Analysis and Modeling for Predicting Long-Term Population

Author

Chen Han-Jun ; Huang Dong-Wei

Author_Institution

Grad. Sch., Tianjin Polytech. Univ., Tianjin, China

Volume

3

fYear

2009

fDate

21-22 May 2009

Firstpage

357

Lastpage

359

Abstract

The mathematical model of population growth is based on logistic equation and BP neural network. The total population is predicted for the next 30 years through the use of Logistic modeling and generalization data. The dynamics of population growth is studied in non-linear dynamic, which pointed out that the problem is the issue of chaos. It is difficult to accurately forecast long-term population. Chaotic neural network will be served as a new research way on population control.

Keywords

backpropagation; chaos; demography; forecasting theory; logistics; neural nets; nonlinear dynamical systems; time series; BP neural network; chaos analysis; chaos modeling; chaotic neural network; logistic equation; logistic generalization; logistic modeling; long-term population forecasting; long-term population prediction; nonlinear dynamics; population growth; Chaos; Computer networks; Differential equations; Logistics; Mathematical model; Mathematics; Neural networks; Nonlinear equations; Predictive models; Shape control; BP neural network; chaos; logistic equation; mathematic model; population prediction;

fLanguage

English

Publisher

ieee

Conference_Titel

Information and Computing Science, 2009. ICIC '09. Second International Conference on

Conference_Location

Manchester

Print_ISBN

978-0-7695-3634-7

Type

conf

DOI

10.1109/ICIC.2009.295

Filename

5168878