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Automatic discovery of the regression model by the means of grammatical and differential evolution

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F14%3A00225536" target="_blank" >RIV/62156489:43110/14:00225536 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Automatic discovery of the regression model by the means of grammatical and differential evolution

  • Original language description

    In the contribution, there is discussed the usage of the method based on the grammatical and differential evolution for the automatic discovery of regression models for discrete datasets. The combination of these two methods enables the process to find the precise structure of the mathematical model and values for the model constants separately. The used method is described and tested on the selected regression examples. The results are reported and the obtained mathematical models are presented. The advantages of the selected approach are described and compared to the classical methods.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2014

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Agricultural Economics-Zemedelska ekonomika

  • ISSN

    0139-570X

  • e-ISSN

  • Volume of the periodical

    60

  • Issue of the periodical within the volume

    12

  • Country of publishing house

    CZ - CZECH REPUBLIC

  • Number of pages

    7

  • Pages from-to

    546-552

  • UT code for WoS article

    347476700002

  • EID of the result in the Scopus database