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International Workshop on Implementing Automata

WIA 1996: Automata Implementation pp 26–34Cite as

Time series forecasting by finite-state automata

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1260))

Abstract

We have developed automata to address the problem of time series forecasting. After turning the time series into sequences of letters, Mohri's algorithm constructs an automaton indexing this text that, once a given word is read, can be used to obtain the set of its positions. By using the automaton to determine what letter usually follows the last sequence of length L, we have developed a one step predictor. This predictor will be used to analyze sunspot activity data.

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References

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Author information

Authors and Affiliations

  1. Laboratoire d'Informatique Ecole d'Ingénieurs en Informatique pour l'Industrie, Université François Rabelais, 64 avenue Jean Portalis, 37200, Tours, France

    Romuald Boné, Christophe Daguin, Antoine Georgevail & Denis Maurel

Authors
  1. Romuald Boné
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  2. Christophe Daguin
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  3. Antoine Georgevail
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  4. Denis Maurel
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Editor information

Darrell Raymond Derick Wood Sheng Yu

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© 1997 Springer-Verlag Berlin Heidelberg

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Boné, R., Daguin, C., Georgevail, A., Maurel, D. (1997). Time series forecasting by finite-state automata. In: Raymond, D., Wood, D., Yu, S. (eds) Automata Implementation. WIA 1996. Lecture Notes in Computer Science, vol 1260. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63174-7_3

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  • DOI: https://doi.org/10.1007/3-540-63174-7_3

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63174-3

  • Online ISBN: 978-3-540-69205-8

  • eBook Packages: Springer Book Archive

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