Graphical method for the knowledge base analysis of the simulation model : доклад, тезисы доклада | Научно-инновационный портал СФУ

Graphical method for the knowledge base analysis of the simulation model : доклад, тезисы доклада

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: Siberian Scientific Workshop on Data Analysis Technologies with Applications, SibDATA 2020; Krasnoyarsk; Krasnoyarsk

Год издания: 2020

Ключевые слова: agent modeling, infographics, knowledge base, simulation modeling, spacecraft onboard equipment

Аннотация: This article presents a method of analysis of the simulation models which are peculiar due to their graphical structure and declarative knowledge bases containing the description of the state of the modeled object and rules of its functioning. The models consist of intellectual agents, each of those having interfaces of external influence perception and being able to influence other agents through the transmission of control commands via the specified switching links. We have formalized the model and criteria of the analysis, defining operations for the model elements in the form convenient for the software implementation. We suggest the data base structure, providing a combination of graphical methods. Software tools have been completed in the form of a web application of an infographics library. Using this method allows us to analyze the structural links of the model, calculate functional load, and reveal errors in the knowledge bases and elements with lacking or excessive parameters and rules. The results of the method operation are interactive graphical presentations and automatically generated tables of errors and recommendations.

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Издание

Журнал: CEUR Workshop Proceedings

Выпуск журнала: 2727

Номера страниц: 25-33

Персоны

  • Isaeva O. (Institute of Computational Modelling of the Siberian Branch,Russian Academy of Sciences)
  • Nozhenkova L. (Institute of Computational Modelling of the Siberian Branch,Russian Academy of Sciences)
  • Kulyasov N. (Institute of Computational Modelling of the Siberian Branch,Russian Academy of Sciences)
  • Isaev S. (Institute of Computational Modelling of the Siberian Branch,Russian Academy of Sciences)

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