In search for new applications of the evidence theory

• Autorzy: Kłopotek M. A. , Wierzchoń S. T.
• Języki publikacji: EN

Abstrakty

EN

This paper is concerned with seeking new applications for the Dempster-Shafer Theory that are by their nature better suited to the axiomatic framework of this theory. In particular, wafer processing on a integrated circuits production line, chemical product quality evaluation etc. are considered. Some extensions to basic DST formalism are envisaged.

Słowa kluczowe

EN

integrated circuits production; chemical product; quality evaluation

• Wydawca: Wydawnictwo Uniwersytetu Przyrodniczo-Humanistycznego w Siedlcach
• Czasopismo: Studia Informatica : systems and information technology
• Rocznik: 2003
• Tom: Vol. 1(1)
• Strony: 27--36
• Opis fizyczny: Bibliogr. 12 poz., rys.

Twórcy

autor

Kłopotek M. A.

• Institute of Computer Science, Polish Academy of Sciences, Warsaw
• Institute of Computer Science, University of Podlasie, Siedlce

autor

Wierzchoń S. T.

• Institute of Computer Science, Polish Academy of Sciences, Warsaw
• Department of Computer Science, Białystok University of Technology, Białystok

Bibliografia

• 1. Jaffray J. Y., Linear utility theory for belief functions, Operations Research Letters 8 (1989) 107-112.
• 2. Klopotek M.A: Methods of Identification and Interpretations of Belief Distributions in the Dempster-Shafer Theory (in Polish). Monograph. Publisher: Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland, 1998, (236 pages).
• 3. Kłopotek M.A.: Dempster-Shafer theory. Encyclopedia of Mathematics. Supplement III. M.Hazenwinkel (ed). KluwerAcademic Publishers, to appear in December 2001.
• 4. Klopotek M.A., Wierzchon S.T.: Empirical Models for the Dempster-Shafer Theory. In Srivastava, R.P.; Mock, T.J., (Eds.): Belief Functions in Business Decisions ISBN: 3-7908-1451-2, Springer-Verlag, volume 88 of the series „Studies in Fuzziness and Soft Computing, to appear March 2002.
• 5. Shenoy P. P., A Comparison of Graphical Techniques for Decision Analysis, European Journal of Operational Research (1994).
• 6. Shenoy P. P., Valuation-based Systems for Bayesian Decision Analysis, Operations Research 40 (1992) 463-484.
• 7. Shenoy, P.P.: „A Fusion Algorithm for Solving Bayesian Decision Problems”, in Uncertainty in Artificial Intelligence, Proceedings of the Seventh Conference, 1991, pp 361-369.
• 8. Strat T., Decision analysis using belief functions, Int. J. of Approximate Reasoning 4 (1990) 391-417. 24.
• 9. Wierzchoń S.T.: Methods of representing and processing of uncertain information within the framework of Dempster-Shafer Theory. Monograph. Publisher: Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland, 1996.
• 10. Xu H., Hsia Y-T. and Smets Ph.: Transferable Belief Model for Decision Making in Valuation-Based Systems, IEEE Trans. on Systems, Man and Cybernetics (1995).
• 11. Xu H., A Decision Calculus for Belief Functions in Valuation-Based Systems, in Dubois D., Wellman M. P., D’Ambrosio B. and Smets Ph. eds. Proc. 8th Uncertainty in Artificial Intelligence (San Mateo, Ca.:Morgan Kaufmann, 1992) 352-359.
• 12. Yager R. R., Decision Making under Dempster-Shafer Uncertainties, Iona College Machine Intelligence Institute Tech. Report MII-915, (1989).