The Research of Time Series Forecasting Model Base on Gene Expression Programming

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Abstract:

With time as the independent variable to model the dynamic system is beneficial for system analysis, and also can provide guidance forecast for the changes of system future. The methods are the basic GEP algorithm based on time series model to predict, this article will give GEP algorithm hybrid model to predict the time series method.

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777-780

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September 2012

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] George G.S. Forecasting. Chaotic Time Series with Genetic Algotithms[J]. Physical Review E, 1997, 55(3): 2557~2567.

Google Scholar

[2] Andrea Tettamanzi. Genetic Programming for Financial Time Series Predicton[C]. Portugal: Springer, Proceedings of EuroGP'2001 , Coimbra, 2001: 361~370.

Google Scholar

[3] I Katya Rodriguez Vazquez. Genetic Programming in Time Series Modeling: an Application to Meteorological Data[C]. Korea: IEEE Press, Proceedings of the 2001 Congress on Evolutionary Computation, 2001: 261~266.

DOI: 10.1109/cec.2001.934399

Google Scholar

[4] Jie Zuo, Chang-jie Tang, Chuan Li, Chang-an Yuan and An-long Chen. Time Series Prediction Based on Gene Expression Programming[C]. Source: In Advances in Web-Age Information Management, Vol 3129 of Lecture Notes in Computer Science, 2004: 55~64.

DOI: 10.1007/978-3-540-27772-9_7

Google Scholar

[5] Lopes H.S. and W.R. Weinert. A Gene Expression Programming System for Time Series Modeling[C]. Source: In Proceedings of XXV Iberian Latin American Congress on Computational Methods in Engineering, CILAMCE 2004, Recife, Brazil, 10-12 November, 2004.

Google Scholar

[6] Li Qu, Cai Zhihua, Jiang Siwei, Zhu Li. Gene Expression Programming in Prediction[C]. Source: In Proceedings of the Fifth World Congress on Intelligent Control and Automation (WCICA), 2004, 3: 2171~2175.

DOI: 10.1109/wcica.2004.1341971

Google Scholar

[7] Li Qu, Cai Zhihua, Zhu Li, Zhao Yunsheng. Application of Gene Expression Programming in Predicting the Amount of Gas Emitted from Coal Face[J]. Journal of Basic Science and Engineering, 2004, 12(1): 49~54.

Google Scholar

[8] Keskin M.E. and Terzi, Modeling Water Temperature Using Gene Expression Programming[J]. Source: In Proceedings of the 14th Turkish Symposium on Artificial Intelligence and Neural Networks, TAINN 2005: 280~285.

Google Scholar

[9] Ferreira,C. Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence[M]. Berlin: Springer-Verlag, 2006: 1~478.

Google Scholar