Abstract
This paper applies the method of assigning probability in Dempster Shafer Theory (DST) to the components of rule-based expert systems used in the control of nuclear reactors. Probabilities are assigned to premises, consequences, and rules themselves. This paper considers how uncertainty can propagate through a system of Boolean equations, such as fault trees or expert systems. The probability masses assigned to primary initiating events in the expert system can be derived from observing a nuclear reactor in operation or based on engineering knowledge of the reactor parts. Use of DST mass assignments offers greater flexibility to the construction of expert systems in two important respects.
Operated by Martin Marietta Energy Systems, Inc., under contract DE-AC05-840R2l400 with the U.S. Department of Energy.
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References
Chatalic, Philippe, Didier Dubois, Henri Prade, (1986), “An Approach to Approximate Reasoning Based on Dempster’s Rule of Combination,” paper presented at RAI/IPAR ’86 Conference on Robotics and Artificial Intelligence, June 18–20, 1986.
Dempster, Arthur P., (1967), “Upper and Lower Probabilities Induced by a Multi-Valued Mapping,” Annals of Mathematical Statistics. Vol. 38, pp. 325–339.
Dubois, Didier, and Henri Prade, (1987), “On the Combination of Uncertain or Imprecise Information,” L.S.I. Report #263, Universite Paul Sabatier, 118 route de Narbonne, 31062 Toulouse Cedex, France, submitted to Inter. Journal of Approximate Reasoning.
Gouvernet, J., S. Ayme, and E. Sanchez, (1982), “Approximate Reasoning in Medical Genetics,” in Fuzzy Set and Possibility Theory: Recent Developments. R. R. Yager (Ed.), (New York: Pergamon Press).
Guth, Michael A. S., (1987), “Uncertainty Analysis of Rule-Based Expert Systems Using Dempster-Shafer Mass Assignments,” Inter. Journal of Intelligent Systems, forthcoming.
Ishizuka, M., K. S. Fu, and J. T. P. Yao, (1981), “SPERIL-1: Computer-based Structural Damage Assessment Systems,” CE-STR-81–36, School of Civil Engineering, Purdue University, West Lafayetta, IN, November 1981.
Lee, Newton S., Yves L. Grize, and Khosrow Dehnad, (1987), “Quantitative Models for Reasoning under Uncertainty in Knowledge-Based Expert Systems,” Inter. Journal of Intelligent Systems. Vol. II, pp. 15–38.
Neuschaefer, Carl H., Peter W. Rzasa, Eugene Filshtein, Richard L. Burrington, and Robert Donais, “Application of C-E’s Generic Diagnostic System to Power Plant Diagnostics,” paper presented at EPRI conference on Expert Systems Applications in Power Plants, Boston, MA, May 1987.
Prade, H., (1985), “A Computational Approach to Approximate and Plausible Reasoning with Applications to Expert Systems,” IEEE Trans. Pattern Anal. Mach. Intel.. Vol. PAMI-7.
Shafer, Glenn, (1976), A Mathematical Theory of Evidence. (Princeton, N.J.: Princeton University Press).(1982), “Bayes’s Two Arguments for the Rule of Conditioning,” Ann. Statistics. Vol. 10, pp. 1075–1089.
“Conditional Probability,” International Statistical Review, Vol. 53, #3, pp. 261–277. “The Combination of Evidence,” Internat. J. Intelligent Systems. Vol. 1, No. 3, pp. 155–179. (1986) with P. P. Shenoy, and K. Mellouli, “Propagating Belief Functions in Qualitative Markhov Trees,” Working Paper No. 186, School of Business, University of Kansas, Lawrence.
Shenoy, P. P. and G. Shafer, “Propagating Belief Functions Using Local Computations,” IEEE Expert. Vol. 1, No. 3, pp. 43–52.
Skatteboe, Rolf, and Grethe Tangen, and Kaj Berge, (1987), “Models Applied in Knowledge Based Diagnosis,” paper presented at EPRI conference on Expert Systems Applications in Power Plants, Boston, Mass.
Zimmerman, H.-J., (1985), Fuzzy Set Theory - and Its Applications. (Boston: Kluwer-Nihoff Publishing Co. 1985).
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© 1988 Plenum Press, New York
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Guth, A.S.M. (1988). Incorporating “Fuzzy” Data and Logical Relations in the Design of Expert Systems for Nuclear Reactors. In: Majumdar, M.C., Majumdar, D., Sackett, J.I. (eds) Artificial Intelligence and Other Innovative Computer Applications in the Nuclear Industry. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-1009-9_48
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DOI: https://doi.org/10.1007/978-1-4613-1009-9_48
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