Abstract
In this paper, we propose an application of genetic programming to economic forecasting that can obviously improve traditional economic forecasting methods; the latter can only obtain rough fitting curves with unsatisfactory results. Forecasted and estimated standard errors are also computed and analyzed. Using practical historical data from Statistical Yearbooks of the People’s Republic of China in recent years, an automatically generated mathematical model of economic forecasting by genetic programming is established. Forecasting results indicate that the accuracy obtained by genetic programming is obviously higher than traditional methods such as linear, exponential, and parabolic regression methods.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This work is partly supported by the National Natural Science Key Foundation of China with the Grant No.60133010 and the National Research Foundation for the Doctoral Program of Higher Education of China with the Grant No.20030486049.
This work is partly supported by the National Natural Science Key Foundation of China with the Grant No.60133010 and the National Research Foundation for the Doctoral Program of Higher Education of China with the Grant No.20030486049.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
K. D. Jong, L. Fogel, H. P. Schwefel, et al., The Hand Book of Evolutionary Computations, IOP Publishing Ltd, Oxford University Press, 1997.
L. Kang, Y. Li, and Y. Chen, A tentative research on complexity of automatic programming, Wuhan University Journal of Natural Science, 6 (2001), 59–62.
J. R. Koza, Genetic Programming I: On the Programming of Computers by Means of Natural Selection, MIT Press, Cambridge, MA, 1992.
J. R. Koza. Genetic Programming III: Darwinian Invention and Problem Solving, San Francisco, Morgan Kaufmann Publishers, 1999.
Z. Pan, L. Kang, and Y. Chen, Evolutionary Computations, Tsinghua University Press, Beijing, China, 1998.
State Statistical Bureau of PRC, Theory of Statistics, Statistical Press of China, 2002.
State Statistical Bureau of PRC, Statistical Yearbook of China, Statistical Press of China, 2002.
Statistical Bureau of Jiangxi Province, Statistical Yearbook of Jiangxi Province, Statistical Press of China, 2002.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Li, K., Chen, Z., Li, Y., Zhou, A. (2005). An Application of Genetic Programming to Economic Forecasting. In: Zhang, W., Tong, W., Chen, Z., Glowinski, R. (eds) Current Trends in High Performance Computing and Its Applications. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-27912-1_7
Download citation
DOI: https://doi.org/10.1007/3-540-27912-1_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25785-1
Online ISBN: 978-3-540-27912-9
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)