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Short Time Series Forecasting Method Based on Genetic Programming and Kalman Filter

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Complex Computational Ecosystems (CCE 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13927))

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Abstract

Accurate forecasting of the baccalaureate admission statistics is a crucial step towards an improvement of the educational system in Mauritania and its responsiveness to the economical needs. Since an available historical information is collected only over last ten years, an accurate forecasting technique for short time series is required. Addressing this issue, the presented paper proposes a tool based on the genetic programming and Kalman filter. This tool allows to make accurate short term prediction for short time series and easily set up experiments. A tool validation on different data sets is presented, where the provided tool provides more robust forecasting results comparatively with the state-of-the-art techniques. It is expected that this tool can help to make a qualitative jump in the improvement of Mauritanian education system.

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Notes

  1. 1.

    https://documents1.worldbank.org/curated/en/982661583533195267/pdf/Mauritania-Enhanced-Heavily-Indebted-Poor-Countries-HIPC-Initiative.pdf.

  2. 2.

    https://documents.worldbank.org/en/publication/documents-reports/documentdetail/819601592919148037.

  3. 3.

    https://robjhyndman.com/hyndsight/short-time-series/.

  4. 4.

    https://otexts.com/fpp2/long-short-ts.html.

  5. 5.

    https://www.cs.unc.edu/~welch/kalman/siam_cipra.html.

  6. 6.

    http://easea.unistra.fr.

  7. 7.

    https://data.worldbank.org/.

  8. 8.

    https://forecasters.org/resources/time-series-data/m3-competition/.

  9. 9.

    https://github.com/robjhyndman/fma.

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Author information

Authors and Affiliations

  1. ICUBE Laboratory, Strasbourg University, Strasbourg, France

    Lalla Aicha Kone, Anna Ouskova Leonteva & Pierre Collet

  2. Reasearch Unit of Scientific Computing, Computer Science and Data Science, University of Nouakchott, Nouakchott, Mauritania

    Lalla Aicha Kone, Mamadou Tourad Diallo & Ahmedou Haouba

Authors
  1. Lalla Aicha Kone
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  2. Anna Ouskova Leonteva
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  3. Mamadou Tourad Diallo
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  4. Ahmedou Haouba
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  5. Pierre Collet
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Corresponding author

Correspondence to Lalla Aicha Kone .

Editor information

Editors and Affiliations

  1. Strasbourg University, Strasbourg, France

    Pierre Collet

  2. Azerbaijan State Oil and Industry University, Baku, Azerbaijan

    Latafat Gardashova

  3. Strasbourg University, Strasbourg, France

    Samer El Zant

  4. French Azerbaijani University, Baku, Azerbaijan

    Ulviya Abdulkarimova

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Kone, L.A., Leonteva, A.O., Diallo, M.T., Haouba, A., Collet, P. (2023). Short Time Series Forecasting Method Based on Genetic Programming and Kalman Filter. In: Collet, P., Gardashova, L., El Zant, S., Abdulkarimova, U. (eds) Complex Computational Ecosystems. CCE 2023. Lecture Notes in Computer Science, vol 13927. Springer, Cham. https://doi.org/10.1007/978-3-031-44355-8_6

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  • DOI: https://doi.org/10.1007/978-3-031-44355-8_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-44354-1

  • Online ISBN: 978-3-031-44355-8

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