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Please use this identifier to cite or link to this item: https://oldena.lpnu.ua/handle/ntb/40448
Title: Logical inference mechanism in situational awareness systems
Authors: Mykich, Khrystyna
Burov, Eugene
Affiliation: Lviv Polytechnic National University
Bibliographic description (Ukraine): Mykich K. Logical inference mechanism in situational awareness systems / Khrystyna Mykich, Eugene Burov // Litteris et Artibus : proceedings, 23–25 November, 2017. — Lviv : Lviv Polytechnic Publishing House, 2017. — P. 418–419. — (9th International academic conference «Computer science & engineering 2017» (CSE-2017)).
Bibliographic description (International): Mykich K. Logical inference mechanism in situational awareness systems / Khrystyna Mykich, Eugene Burov // Litteris et Artibus : proceedings, 23–25 November, 2017. — Lviv : Lviv Polytechnic Publishing House, 2017. — P. 418–419. — (9th International academic conference «Computer science & engineering 2017» (CSE-2017)).
Is part of: Litteris et Artibus : матеріали, 2017
Litteris et Artibus : proceedings, 2017
Conference/Event: 7th International youth science forum «Litteris et Artibus»
Journal/Collection: Litteris et Artibus : матеріали
Issue Date: 23-Dec-2017
Publisher: Видавництво Львівської політехніки
Lviv Polytechnic Publishing House
Place of the edition/event: Львів
Lviv
Temporal Coverage: 23–25 листопада 2017 року
23–25 November, 2017
Keywords: situation assessment
situational awareness
ontology
logical inference
granular computing
Number of pages: 2
Page range: 418-419
Start page: 418
End page: 419
Abstract: In the article are described problems related to creation and maintenance of situational awareness systems. An approach based on situational knowledge representation with ontological models is selected for attaining situational awareness in complex intelligent enterprise systems, where objects can be in several situations in the same time and some situations are defined imprecisely. Granular computing approach is used for reduction of situational knowledge management complexity.
URI: https://ena.lpnu.ua/handle/ntb/40448
ISBN: 978-966-941-108-2
Copyright owner: © Національний університет “Львівська політехніка”, 2017
References (Ukraine): [1] Burov Y. Algebraic model for knowledge representation in situational awareness systems / Y. Burov, Kh. Mykich // XIth International Scientific and Technical Conference Computer Sciences and Information Technologies (CSIT). – Lviv Polytechnic Publishing House, 2016. – P. 165 – 167.
[2] Burov Y. Algebraic framework for knowledge processing in systems with situational awareness / Y. Burov, Kh. Mykich // Advances in Intelligent Systems and Computing. Advances in Intelligent Systems and Computing 512. – ISSN 2194-5357. – DOI 10.1007/978-3-319-45991-2_18. – Springer International Publishing AG 2017. – P. 217 – 227.
[3] Burov Y. The approach of granular computing and rough sets for identifying situations / Yevhen Burov, Khrystyna Mykich // ECONTECHMOD. An international quarterly journal, Vol. 6, No. 2, 2017. – P. 45–50.
[4] Settembre G. P. Multi-agent approach to Situation Assessment / G. P. Settembre. – University “Sapienza” of Rome, 2007. – P. 1 – 106.
[5] Lytvyn V. Design of intelligent decision support systems using ontological approach / V. Lytvyn // ECONTECHMOD. An international quarterly journal Vol. 2, №1, 2013. – P. 31-37.
[6] Zavuschak I. The context analysis and the process of its formation / I. Zavuschak // ECONTECHMOD. An international quarterly journal, Vol. 6, No. 2, 2017. – P. 67–72.
[7] Yao Y. Information granulation and rough set approximation / Y.Y. Yao // International Journal of Intelligent Systems, Vol. 16, No. 1, 2001. – P. 87- 104.
[8] Minaiev Y. Structured fs-granules in problems of granular computing / Minaiev Y., Filimonova O. and Minaieva Y. // Electronic modeling. V.37, №1, 2015. – P. 77 – 95. (in Russian).
[9] Yao J.T. Information Granulation and Granular Relationships / J.T. Yao // In Proceedings of the IEEE-Conference on Granular Computing, 2005. – P. 326 – 329.
References (International): [1] Burov Y. Algebraic model for knowledge representation in situational awareness systems, Y. Burov, Kh. Mykich, XIth International Scientific and Technical Conference Computer Sciences and Information Technologies (CSIT), Lviv Polytechnic Publishing House, 2016, P. 165 – 167.
[2] Burov Y. Algebraic framework for knowledge processing in systems with situational awareness, Y. Burov, Kh. Mykich, Advances in Intelligent Systems and Computing. Advances in Intelligent Systems and Computing 512, ISSN 2194-5357, DOI 10.1007/978-3-319-45991-2_18, Springer International Publishing AG 2017, P. 217 – 227.
[3] Burov Y. The approach of granular computing and rough sets for identifying situations, Yevhen Burov, Khrystyna Mykich, ECONTECHMOD. An international quarterly journal, Vol. 6, No. 2, 2017, P. 45–50.
[4] Settembre G. P. Multi-agent approach to Situation Assessment, G. P. Settembre, University "Sapienza" of Rome, 2007, P. 1 – 106.
[5] Lytvyn V. Design of intelligent decision support systems using ontological approach, V. Lytvyn, ECONTECHMOD. An international quarterly journal Vol. 2, No 1, 2013, P. 31-37.
[6] Zavuschak I. The context analysis and the process of its formation, I. Zavuschak, ECONTECHMOD. An international quarterly journal, Vol. 6, No. 2, 2017, P. 67–72.
[7] Yao Y. Information granulation and rough set approximation, Y.Y. Yao, International Journal of Intelligent Systems, Vol. 16, No. 1, 2001, P. 87- 104.
[8] Minaiev Y. Structured fs-granules in problems of granular computing, Minaiev Y., Filimonova O. and Minaieva Y., Electronic modeling. V.37, No 1, 2015, P. 77 – 95. (in Russian).
[9] Yao J.T. Information Granulation and Granular Relationships, J.T. Yao, In Proceedings of the IEEE-Conference on Granular Computing, 2005, P. 326 – 329.
Content type: Conference Abstract
Appears in Collections:Litteris et Artibus. – 2017 р.

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