DocumentCode
2912214
Title
World population projections using metabolic GM (1,1) model
Author
Lu, Caimei ; Hao, Yonghong ; Wang, Xuemeng
Author_Institution
Shanxi Univ., Taiyuan
fYear
2007
fDate
18-20 Nov. 2007
Firstpage
453
Lastpage
457
Abstract
Forecasts of population size allow city planners, economists, public agencies, environmentalists, and social scientists to prepare for what is to come, so the research on population projections has become a focus of demographers´ research. In the study, population system is regarded as a grey system and a method based on GM (1,1) model from Grey system theory is introduced to population projections. Two key aspects of the method are crucial for obtaining best accuracy of prediction. They are the choice of the length for the original data to be used in the model and the adoption of the metabolic GM (1,1) model in prediction. The former determines what initial data to be used while the latter describes an iteration process on how to proceed to predict. The method is then applied to the projections of world population. The results show that in 2012 world population will surpass 7 billion; in 2029 it will grow beyond 8 billion and in 2050 it will be between 8.9 and 9.4 billion, which is in accordance with the latest projections from the UN. The findings show the metabolic GM (1,1) model is an effective mathematical means in population projections.
Keywords
demography; differential equations; grey systems; time series; demography; differential equation; grey system; iteration process; metabolic GM (1,1) model; population size forecast; population system; social science; time series; world population projection; Cities and towns; Differential equations; Error analysis; Intelligent structures; Intelligent systems; Predictive models; Probability; Statistical analysis; Uncertain systems; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Grey Systems and Intelligent Services, 2007. GSIS 2007. IEEE International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4244-1294-5
Electronic_ISBN
978-1-4244-1294-5
Type
conf
DOI
10.1109/GSIS.2007.4443316
Filename
4443316
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