Abstract
For time series data mining (TSDM), the problem of time series forecasting has attracted wide attention as solving it actually paves a way to extrapolate past behavior into the future. Researchers have long been interested in modeling the problem by linear regression, neural network, chaos, support vector machines, etc. In this paper, we explore the use of Moore automata for time series forecast modeling and demonstrate how the Moore automata can be converted to solve the problem with regression methods. The effectiveness of the proposed approach has been verified by experiments.
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
Xinning, S., Jianglin, Y., et al.: Data Mining Theory and Technology. Science Technology Press, Beijing (2003)
Pengtao, J., Huacan, H., Li, L., Tao, S.: Overview of Time Series Data Mining. J. Application Research of Computer 24, 15–18 (2007)
Wenlong, Q., Haiyan, L., Wei, Y., et al.: Research on Multi-scale Prediction of Time Series based on Wavelet and Support Vector Machines. J. Computer Engineering and Applications 43, 182–185 (2007)
Edward, F.M.: Mind-Experiments on Sequential Machines. J. Automata Studies, 129–153 (1956)
Istvn, B.: Equivalence of Mealy and Moore automata. J. Acta Cybernetica 14, 541–552 (2001)
Fusheng, T.: Modeling Dynamical Systems by Recurrent Neural Networks. Technical report, University of California, San Diego (1994)
George, E.P.B., Gwilym, M.J., Gregory, C.R.: Time Series Analysis Forecasting and Control. Prentice-Hall, New Jersey (1994)
Programmers United Develop Net, http://www.pudn.com
Leona, S.A., Stephen, G.W.: Multiple Regression: Testing and Interpreting Interactions. Sage, USA (1991)
Xingli, B., Chengjian, Z.: Research on Time Series Forecasting Model Based on Support Vector Machines. In: 2010 International Conference on Measuring Technology and Mechatronics Automation, pp. 227–230. IEEE Press, Changsha (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chen, Y., Wu, Z., Li, Z., Zhang, Y. (2010). Research on Time Series Forecasting Model Based on Moore Automata. In: Cao, L., Feng, Y., Zhong, J. (eds) Advanced Data Mining and Applications. ADMA 2010. Lecture Notes in Computer Science(), vol 6440. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17316-5_9
Download citation
DOI: https://doi.org/10.1007/978-3-642-17316-5_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17315-8
Online ISBN: 978-3-642-17316-5
eBook Packages: Computer ScienceComputer Science (R0)