Conditional contradictions in diagnostic knowledge bases

• Autorzy: Cholewa W.
• Konferencja: International Symposium on Compressor & Turbine Flow Systems Theory & Application Areas "SYMKOM" (11 ; 20-23.10.2014 ; Łódź, Polska)
• Języki publikacji: EN

Abstrakty

EN

A recognition of the actual technical state of an object is possible by means of diagnostic expert systems. Knowledge bases of such systems are collected by teams of experts and unfortunately they are not free from errors. Identification of errors, and in particular identification of conditional errors is a very hard task. The paper introduces a measure called disagreement level and enabling identification of erroneous data as well as errors in models represented by means of diagnostic knowledge bases.

Słowa kluczowe

EN

knowledge base; intuitionistic statement network; disagreement level; diagnostic system

PL

baza wiedzy; sieci intuicjonistyczne; system diagnostyczny

• Wydawca: Wydawnictwo Politechniki Łódzkiej
• Czasopismo: Zeszyty Naukowe. Cieplne Maszyny Przepływowe - Turbomachinery / Politechnika Łódzka
• Rocznik: 2014
• Tom: nr 145
• Strony: 33--34
• Opis fizyczny: Bibliogr. 10 poz.

Twórcy

autor

Cholewa W.

• Institute of Fundamentals of Machinery Design Silesian University of Technology Gliwice, Poland

Bibliografia

• [1] Cholewa W.: Dynamical Statement Networks, In: Awrejcewicz J. (Ed.), Applied Non-Linear Dynamical Systems, Springer 2014 (in press).
• [2] Bargiela A., Pedrycz W.: Granular Computing. An Introduction.
• [3] Cholewa W.: Multimodal statement networks for diagnostic applications, In: Proceedings of the International Conference on Noise and Vibration Engineering (ISMA), pp. 817-830, 2010.
• [4] Cholewa W.: Intuitionistic Notice Boards for Expert Systems, In: Gruca A. et al. (Eds.), Man-Machine Interactions 3, Advances in Intelligent Systems and Computing 241, Springer 2014.
• [5] Jensen V.J.: Bayesian Networks and Decision Graphs, Springer, New York 2002.
• [6] Atanassov K.T.: Intuitionistic Fuzzy Sets. Theory and Applications. Springer Verlag, Berlin Heidelberg, 1999.
• [7] Atanassov K.T.: On Intuitionistic Fuzzy Sets Theory. Springer Verlag, Berlin Heidelberg, 2012.
• [8] Cholewa W.: Mechanical analogy of statement networks. International Journal of Applied Mathematics and Computer Science 18(4), pp. 477-486, 2008.
• [9] Rogala T., Amarowicz M.: Multimodal Statement Network for Organic Rankine Cycle Diagnostic. Use Case of Diagnostic Modeling, Proceedings of the IEEE Intelligent Systems, Warsaw 2014 (in press).
• [10] Cholewa W., Amarowicz M., Chrzanowski P., Rogala T.: Development environment for diagnostic multimodal statement networks, Key Engineering Materials 588, Trans Tech Publications, pp. 74-83, 2014.