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A fractal structure of time series and prediction (a comparative study to neural network)

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F10%3AA1100YDC" target="_blank" >RIV/61988987:17310/10:A1100YDC - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    A fractal structure of time series and prediction (a comparative study to neural network)

  • Original language description

    We develop two models for analysis and forecasting of financial time series. The first model is based on Elliott waves, which disposes of fractal structure. The second one uses an artificial neural network that is adapted by backpropagation. The Elliottwave principle is a detailed description of how financial markets behave. Artificial neural networks are suitable for predicting time series because are able to generalize and are resistant to noise. This paper also includes experimental results of timeseries prediction carried out with both mentioned models.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2010

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Mendel 2010

  • ISBN

    978-80-214-4120-0

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

  • Publisher name

    Brno Univerzity of Technology

  • Place of publication

    Brno

  • Event location

    Brno

  • Event date

    Jun 23, 2010

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000288144100020