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Comparison of artificial neural networks using prediction benchmarking

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F11%3A43866683" target="_blank" >RIV/70883521:28140/11:43866683 - isvavai.cz</a>

  • Alternative codes found

    RIV/70883521:28110/11:43866683

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Comparison of artificial neural networks using prediction benchmarking

  • Original language description

    Artificial neural networks are commonly used for prediction of various time series, linear and nonlinear systems. Nevertheless, the choice of proper type of artificial neural networks is difficult task, because each class of artificial neural networks has different features and abilities. Aim of this paper is to compare and benchmark four typical categories of artificial neural networks in artificial time series prediction and provide suggestions for this kind of applications.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JP - Industrial processes and processing

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2011

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Recent Researches in Automatic Control

  • ISBN

    978-1-61804-004-6

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    152-157

  • Publisher name

    WSEAS Press

  • Place of publication

    Montreux

  • Event location

    Lanzarote

  • Event date

    May 27, 2011

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article