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Sales time series modeling using Box-Jenkins methodology and rbf neural networks

Result description

We examine the class of RBF neural network models for the approximation models of a sales time series provided by a firm and make comparisons their approximation accuracy with the models based on the Box-Jenkins methodology. The similarity between RBF networks and fuzzy models is noted. Time series approximation by applying RBF neural networks or fuzzy models and comparisons between two types of RBF networks and statistical models are discussed at length. Using the disposable data a very appropriate model is the soft RBF network. It is also interesting to note that the most computationally intensive models, i. e. models based on the Box-Jenkins methodology, is newer considered ?best?

Keywords

Time series modelingRBF neural networksFuzzy logic RBF network

The result's identifiers

Alternative languages

  • Result language

    angličtina

  • Original language name

    Sales time series modeling using Box-Jenkins methodology and rbf neural networks

  • Original language description

    We examine the class of RBF neural network models for the approximation models of a sales time series provided by a firm and make comparisons their approximation accuracy with the models based on the Box-Jenkins methodology. The similarity between RBF networks and fuzzy models is noted. Time series approximation by applying RBF neural networks or fuzzy models and comparisons between two types of RBF networks and statistical models are discussed at length. Using the disposable data a very appropriate model is the soft RBF network. It is also interesting to note that the most computationally intensive models, i. e. models based on the Box-Jenkins methodology, is newer considered ?best?

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    AH - Economics

  • OECD FORD branch

Result continuities

Others

  • Publication year

    2009

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Applied Natural Sciences 2009

  • ISBN

    978-80-8105-127-2

  • ISSN

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

  • Publisher name

    University of SS. Cyril and Methodius in Trnava, Faculty of Natural Sciences

  • Place of publication

    Trnava

  • Event location

    Trnava

  • Event date

    Jan 1, 2009

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article