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Machine learning forecasting of CR and PRC balance of trade

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F75081431%3A_____%2F20%3A00002077" target="_blank" >RIV/75081431:_____/20:00002077 - isvavai.cz</a>

  • Alternative codes found

    RIV/61384399:31110/20:00055745

  • Result on the web

    <a href="https://www.shs-conferences.org/articles/shsconf/pdf/2020/01/shsconf_ies_2019_01004.pdf" target="_blank" >https://www.shs-conferences.org/articles/shsconf/pdf/2020/01/shsconf_ies_2019_01004.pdf</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Machine learning forecasting of CR and PRC balance of trade

  • Original language description

    The authors aim is to use machine learning forecasting for predicting the balance of trade of the Czech Republic (CR) and the People´s Republic of China (PRC) through analysing and machine learning.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    50200 - Economics and Business

Result continuities

  • Project

  • Continuities

    N - Vyzkumna aktivita podporovana z neverejnych zdroju

Others

  • Publication year

    2020

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    SHS Web of Conferences: Innovative Economic Symposium - Potential of Eurasian Economic Union (IES)

  • ISBN

    9782759890941

  • ISSN

  • e-ISSN

  • Number of pages

    16

  • Pages from-to

  • Publisher name

    EDP Sciences

  • Place of publication

    Les Ulis, France

  • Event location

    České Budějovice, Česká republika

  • Event date

    Nov 7, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000648964700004