Simulation Model Validation based on Ontological Engineering Methods

Elena Zamyatina, Denis Churin, Viacheslav Lanin, Lyudmila Lyadova, Nada Matta

2022

Abstract

A task of the simulation models examination (verification and validation, V&V) is considered. At the V&V process the correspondence degree of the simulation model created by developers to the simulated object, that description is presented in the form of a conceptual model built by customers, is determined. An ontological approach is proposed to determine the semantic proximity of the simulation model and the conceptual model, whose descriptions are presented in the form of ontologies. Matching rules can also be defined with ontology based on the metrics chosen by the customer. The approach has been tested using the simulation system Triads. The results of the matching algorithm execution are illustrated by an example. The article provides description of the simulation model ontology created in TriadNS and conceptual model ontology, developed with MASK method. The metrics used for proximity assessment are described.

Paper Citation

in Harvard Style

Zamyatina E., Churin D., Lanin V., Lyadova L. and Matta N. (2022). Simulation Model Validation based on Ontological Engineering Methods. In Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - Volume 2: KEOD; ISBN 978-989-758-614-9, SciTePress, pages 237-244. DOI: 10.5220/0011589000003335

in Bibtex Style

@conference{keod22,
author={Elena Zamyatina and Denis Churin and Viacheslav Lanin and Lyudmila Lyadova and Nada Matta},
title={Simulation Model Validation based on Ontological Engineering Methods},
booktitle={Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - Volume 2: KEOD},
year={2022},
pages={237-244},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011589000003335},
isbn={978-989-758-614-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - Volume 2: KEOD
TI - Simulation Model Validation based on Ontological Engineering Methods
SN - 978-989-758-614-9
AU - Zamyatina E.
AU - Churin D.
AU - Lanin V.
AU - Lyadova L.
AU - Matta N.
PY - 2022
SP - 237
EP - 244
DO - 10.5220/0011589000003335
PB - SciTePress