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Knowledge Coding Methods for Rule-Based Expert Systems

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F10%3APU88093" target="_blank" >RIV/00216305:26220/10:PU88093 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Knowledge Coding Methods for Rule-Based Expert Systems

  • Original language description

    This paper gives an overview of knowledge representation methods that are currently being implemented for use in a hybrid expert system shell that has been under development at the Department of Control and Instrumentation, BUT. Two approaches are discussed - a diagnostic and a planning expert system knowledge base coding. A new method suitable for diagnostic rule-based expert systems with automated weight tuning, deriving from neural networks, is proposed. Next, an approach to modeling knowledge basesusing Petri Nets is discussed and inference engine operations are compared for both diagnostic and planning expert system.

  • Czech name

  • Czech description

Classification

  • Type

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

  • CEP classification

    JC - Computer hardware and software

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2010

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    WSEAS Transactions on Information Science and Applications

  • ISSN

    1790-0832

  • e-ISSN

  • Volume of the periodical

    2010

  • Issue of the periodical within the volume

    10

  • Country of publishing house

    GR - GREECE

  • Number of pages

    14

  • Pages from-to

  • UT code for WoS article

  • EID of the result in the Scopus database