The use of text models in the formation of heuristics to solve tasks of diagnosing technical objects

• Autorzy: Korostil J. , Korostil O.

Identyfikatory

DOI

10.17402/144

• Języki publikacji: EN

Abstrakty

EN

This paper describes research related to the use of heuristics in diagnostic tasks of complex technical objects. To build heuristics, the use of text models for technical objects is proposed. Therefore, this paper examines output methods of heuristics from text models and their transformation into logical formulae suitable for use in diagnostic algorithms. Analysis has been carried out for tasks solved during diagnostics, and methods of using heuristics in certain tasks have been reviewed. It is proposed to use heuristics for decision making while implementing certain algorithm steps of monitoring tasks for diagnostic parameters that are solved during diagnostics.

Słowa kluczowe

EN

heuristics; diagnostics; monitoring; malfunction; complex technical object

• Wydawca: Wydawnictwo Naukowe Akademii Morskiej w Szczecinie
• Czasopismo: Zeszyty Naukowe Akademii Morskiej w Szczecinie
• Rocznik: 2016
• Tom: nr 47 (119)
• Strony: 22--28
• Opis fizyczny: Bibliogr. 11 poz.

Twórcy

autor

Korostil J.

• Maritime University of Szczecin 1–2 Wały Chrobrego St., 70-500 Szczecin, Poland

autor

Korostil O.

• Ukrainian Printing Academy, Lviv, Ukraine

Bibliografia

• 1. Korbic, J., Kościelny, J.M., Kowalczyk, Z. & Cholewa, W. (Eds) (2002) Diagnostyka procesów. Modele. Metody sztucznej inteligencji. Zastosowania. Warszawa: WNT.
• 2. Korostil, O. (2012) Tools of descriptions of methods of text model synthesis with text information streams. Modelling and information technologies: collected articles. G. Puchov IPME of National Academy of Sciences of Ukraine 65. pp. 95–104.
• 3. Korostil, O. (2013) Analysis of parameters of text forms of representing the information. Collected articles. G. Puchov IPME of National Academy of Sciences of Ukraine 67. pp. 89–97.
• 4. Korostil, Y. & Korostil, O. (2012) Analysis and interpretation of text models. Journal of KONBIN N4(24). Safety and reliability systems. Warszawa: Wydawnictwo Instytutu Technologicznego Wojsk Lotniczych. pp. 51–56.
• 5. Korostil, Y. & Korostil, O. (2013) Methods and extension of abilities of text model semantic analysis. Scientific Journals Maritime University of Szczecin 35 (107). pp. 90–96. 6. McDermott, D. (1982) Non-monotonie logic: non-monotonie modal theories. J.ACM. 29, 1. pp. 34–57.
• 7. Michalewicz, Z. & Fogel, D.B. (2006) Jak to rozwiązać, czyli nowoczesna heurystyka. Warszawa: WNT.
• 8. Mordechai, B.A. (2005) Logika matematyczna w informatyce. Warszawa: WNT.
• 9. Reiter, R.A. (1980) Logic for default reasoning. Artificial Intelligence 13, 1–2. pp. 81–131.
• 10. Slupiecki, J., Halkowska, K. & Pirog-Rzepecka, K. (1999) Logika matematyczna. Warszawa: WN.
• 11. Thayse, A., Gribomont, P., Louis, G., Snyers, D., Wodon, P., Gochet, P., Gregoire, E., Sanchez, E. & Delsarte, P. (1990) Logical approach to the artificial intelligence: from classical logics to logical programming. Moscow: Mir.

Uwagi

EN

Marine Technology and Innovation

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017)