Abstract
The purpose of this article is to demonstrate a way of intellectualization of automated information and diagnostic systems using knowledge bases, databases and algorithms for the formalization of procedures in terms of the development of an expert system for marine diesel engines.
The aim of this work is to develop an expert system’s architecture with data mining tools for solving the problem of technical exploitation of marine diesel engines based on fragmented, unreliable and possibly inaccurate information. The architecture of such expert system allows moving from normal monitoring to ≪information monitoring≫ in the specialized intelligent human-machine systems. Application of data mining technology allows optimizing database processing queries that retrieve the required information from the actual data in order to detect important patterns. An approach based on data mining and fuzzy logic in the expert system is shown on an example of solving technical exploitation of marine diesel engines problem.
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References
Kureichik, V.M.: Features of decision making support system design. Izvestiya SFedU. Engineering Sciences (7), 92–98 (2012)
Kureichik, V.M., Polkovnikova, N.A.: Development of hybrid expert system for main marine diesel engines. In: XVI International Conference on Soft Computing and Measurements (SCM 2013), May 23-25, pp. 27–30 (2013)
Polkovnikova, N.A., Kureichik, V.M.: Development of an expert system model based on fuzzy logic. Izvestiya SFedU. Engineering Sciences 1(150), 83–92 (2014)
Miller, G.A. The magic number seven plus or minus two: some limits on our capacity for processing information. Psychological Review (63), 81 – 97 (1956)
Li, D., Du, Y.: Artificial intelligence with uncertainty, p. 347. Tsinghua University, Beijing, Chapman & Hall/CRC (2008)
Zadeh, L.A.: Is there a need for fuzzy logic? Information Sciences 178, 2751–2779 (2008)
Pegat, A.: Fuzzy modeling and control M.: BINOM. Laboratory of Knowledge, p. 798 (2009)
Sivanandam, S.N., Sumathi, S., Deepa, S.N.: Introduction to fuzzy logic using MATLAB, p. 441. Springer (2007)
Buckley, J.J., Jowers, L.J.: Simulating continuous fuzzy systems, p. 202. Springer (2006)
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© 2014 Springer International Publishing Switzerland
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Polkovnikova, N.A., Kureichik, V.M. (2014). Hybrid Expert System Development Using Computer-Aided Software Engineering Tools. In: Kravets, A., Shcherbakov, M., Kultsova, M., Iijima, T. (eds) Knowledge-Based Software Engineering. JCKBSE 2014. Communications in Computer and Information Science, vol 466. Springer, Cham. https://doi.org/10.1007/978-3-319-11854-3_37
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DOI: https://doi.org/10.1007/978-3-319-11854-3_37
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11853-6
Online ISBN: 978-3-319-11854-3
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