Approximations for efficient computation in the theory of evidence
作者： Bj∅rnar Tessem
DOI: 10.1016/0004-3702(93)90072-J
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摘要: The theory of evidence has become a widely used method for handling uncertainty in intelligent systems. The method has, however, an efficiency problem. To solve this problem there is …
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sci-hub.se 参考文章(11)
Philippe Smets, Belief functions versus probability functions Uncertainty and Intelligent Systems. pp. 17- 24 ,(1988) , 10.1007/3-540-19402-9_51
Glenn Shafer, Belief Functions and Parametric Models Journal of the royal statistical society series b-methodological. ,vol. 44, pp. 265- 290 ,(1982) , 10.1007/978-3-540-44792-4_10
Jeffrey A. Barnett, Computational Methods for A Mathematical Theory of Evidence Classic Works of the Dempster-Shafer Theory of Belief Functions. pp. 197- 216 ,(1981) , 10.1007/978-3-540-44792-4_8
Prakash P. Shenoy, Glenn Shafer, Khaled Mellouli, Propagation of Belief Functions: A Distributed Approach Uncertainty in Artificial Intelligence. ,vol. 5, pp. 325- 335 ,(1988) , 10.1016/B978-0-444-70396-5.50033-9
Robert Kennes, Philippe Smets, Fast algorithms for Dempster-Shafer theory Uncertainty in Knowledge Bases. pp. 14- 23 ,(1990) , 10.1007/BFB0028102
DIDIER DUBOIS, HENRI PRADE, A NOTE ON MEASURES OF SPECIFICITY FOR FUZZY SETS International Journal of General Systems. ,vol. 10, pp. 279- 283 ,(1985) , 10.1080/03081078508934893
Frans Voorbraak, A computationally efficient approximation of Dempster-Shafer theory International Journal of Human-computer Studies \/ International Journal of Man-machine Studies. ,vol. 30, pp. 525- 536 ,(1989) , 10.1016/S0020-7373(89)80032-X
L.A. Zadeh, Fuzzy sets as a basis for a theory of possibility Fuzzy Sets and Systems. ,vol. 100, pp. 9- 34 ,(1999) , 10.1016/S0165-0114(99)80004-9
Glenn Shafer, Roger Logan, Implementing Dempster's rule for hierarchial evidence Artificial Intelligence. ,vol. 33, pp. 271- 298 ,(1987) , 10.1016/0004-3702(87)90040-3
Jean Gordon, Edward H. Shortliffe, A method for managing evidential reasoning in a hierarchical hypothesis space Artificial Intelligence. ,vol. 26, pp. 323- 357 ,(1985) , 10.1016/0004-3702(85)90064-5