Organization of information support for business processes at aviation enterprises by means of ontological engineering
DOI:
https://doi.org/10.15587/1729-4061.2018.126673Keywords:
aviation enterprises, language of operating semantics, decision support system, ontological engineeringAbstract
We propose using the deductive principle of inference, which takes into consideration child relations between concepts of a subject domain in the process of forming a reasoning chain and, thus, ensures correctness of knowledge, contained in an ontological system. In this case, an ontological system is directly the intelligence core of a decision support system for organization of business processes at an aviation enterprise. For implementation of the declared principle, three methods of knowledge manipulation in the environment of an ontological system were proposed: bottom-up, top-down and combined, which implies the alternating use of the first two methods. Application of the combined method gives the possibility to eliminate knowledge incompleteness and inconsistency. Formalization of inference process on the knowledge in the environment of an ontological system with the use of the proposed methods is based on a description of the internal relations between concepts, integrating a set of concepts and fields with the help of the language of operational semantics, as well as on the introduction of external relations that characterize structural relations of concepts, including hierarchical relations of aggregation and synthesis.
The possibility of re-using, that is the multiple use of ontological information structures in making decisions on organization of business processes at aviation enterprises will make it possible to enhance efficiency of production decisions and their operative making.
The obtained results create the methodological basis for the development of software of inference organization on knowledge directly in the environment of ontologies, which is proposed to use as part of the core of production DSS.
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Copyright (c) 2018 Igor Shostak, Mariia Danova, Yuri Romanenkov, Oleg Bugaienko, Maksym Volk, Marina Karminska-Bielobrova
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