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An Attempt to Use Self-Adapting Genetic Algorithms to Optimize Fuzzy Systems for Predicting from a Data Stream

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Book cover New Research in Multimedia and Internet Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 314))

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Abstract

In this chapter we present the continuation of our research into prediction from a data stream of real estate sales transactions using ensembles of regression models. The method consists in building models over the chunks of a data stream determined by a sliding time window and incrementally expanding an ensemble by systematically generated models in the course of time. The aged models are utilized to compose ensembles and their output is updated with trend functions reflecting the changes of prices in the market. In the study reported we attempted to incorporate self-adapting techniques into genetic fuzzy systems aimed to construct base models for property valuation. Six self-adapting genetic algorithms with varying mutation, crossover, and selection were developed and tested using real-world datasets. The analysis of experimental results was made employing non-parametric statistical techniques devised for multiple N×N comparisons.

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Author information

Authors and Affiliations

  1. Department of Spatial Management, Wrocław University of Environmental and Life Sciences, Wrocław, Poland

    Tadeusz Lasota

  2. Institute of Informatics, Wrocław University of Technology, Wyb. Wyspiańskiego 27, 50-370, Wrocław, Poland

    Magdalena Smętek & Bogdan Trawiński

  3. Faculty of Electronics, Wrocław University of Technology, Wyb. Wyspiańskiego 27, 50-370, Wroclaw, Poland

    Grzegorz Trawiński

Authors
  1. Tadeusz Lasota
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  2. Magdalena Smętek
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  3. Bogdan Trawiński
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  4. Grzegorz Trawiński
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Corresponding author

Correspondence to Tadeusz Lasota .

Editor information

Editors and Affiliations

  1. Division of Information Systems, Wroclaw University of Technology Institute of Informatics, Wrocław, Poland

    Aleksander Zgrzywa

  2. Division of Information Systems Institute of Informatics, Wroclaw University of Technology, Wrocław, Poland

    Kazimierz Choroś

  3. Division of Information Systems Institute of Informatics, Wroclaw University of Technology, Wrocław, Poland

    Andrzej Siemiński

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Lasota, T., Smętek, M., Trawiński, B., Trawiński, G. (2015). An Attempt to Use Self-Adapting Genetic Algorithms to Optimize Fuzzy Systems for Predicting from a Data Stream. In: Zgrzywa, A., Choroś, K., Siemiński, A. (eds) New Research in Multimedia and Internet Systems. Advances in Intelligent Systems and Computing, vol 314. Springer, Cham. https://doi.org/10.1007/978-3-319-10383-9_8

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  • DOI: https://doi.org/10.1007/978-3-319-10383-9_8

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10382-2

  • Online ISBN: 978-3-319-10383-9

  • eBook Packages: EngineeringEngineering (R0)

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