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Implementation of Neural Networks for Prediction of Chemical Composition of Refining Slag

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27360%2F10%3A86076156" target="_blank" >RIV/61989100:27360/10:86076156 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Implementation of Neural Networks for Prediction of Chemical Composition of Refining Slag

  • Original language description

    Contribution deals with problems of application of artificial neural networks for prediction of chemical composition of refining slag with aim to optimize production process and to improve economy of production. Results of neural networks, which inputs were created from different combination of data, are compared in the contribution. The first priority of prediction accuracy was accentuated to these three components if refining slag: SiO2, Al2O3 and CaO. These predictions must be as accurate as possible, because ternary diagram of temperature of refining slag is drafted from these three components.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JG - Metallurgy, metal materials

  • 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

    METAL 2010

  • ISBN

    978-80-87294-17-8

  • ISSN

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

  • Publisher name

    TANGER, spol. s r.o.

  • Place of publication

    Ostrava

  • Event location

    Rožnov pod Radhoštěm

  • Event date

    May 18, 2010

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article