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Time Series Prediction Using New Adaptive Kernel Estimators

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Computer Recognition Systems 3

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 57))

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Summary

This short article describes two kernel algorithms of the regression function estimation. First of them is called HASKE and has its own heuristic of the h parameter evaluation. The second is a hybrid algorithm that connects SVM and the HASKE in such way that the definition of local neighborhood bases on the definition of the h–neighborhood from HASKE. Both of them are used as predictors for time series.

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Author information

Authors and Affiliations

  1. Silesian Insitute of Technology, Institute of Computer Science, ul. Akademicka 16, 44-100, Gliwice, Poland

    Marcin Michalak

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  1. Marcin Michalak
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Editors and Affiliations

  1. Wroclaw University of Technology, WybrzezeWyspianskiego 27, 50-370, Wroclaw, Poland

    Marek Kurzynski  & Michal Wozniak  & 

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Michalak, M. (2009). Time Series Prediction Using New Adaptive Kernel Estimators. In: Kurzynski, M., Wozniak, M. (eds) Computer Recognition Systems 3. Advances in Intelligent and Soft Computing, vol 57. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-93905-4_26

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  • DOI: https://doi.org/10.1007/978-3-540-93905-4_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-93904-7

  • Online ISBN: 978-3-540-93905-4

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