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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Sebbak, F. Benhammadi, F. Mokhtari, A. Chibaniz, A. Amirat, Y. |
| Copyright Year | 2013 |
| Description | Author affiliation: AI Lab., Ecole Militaire Polytech., Algiers, Algeria (Sebbak, F.; Benhammadi, F.) || LRIA Lab., USTHB Univ., Algiers, Algeria (Mokhtari, A.) || LISSI Lab., Univ. Paris-Est Creteil, Paris, France (Chibaniz, A.; Amirat, Y.) |
| Abstract | The evidence theory and its variants are mathematical formalisms used to represent uncertain as well as ambiguous data. The evidence combination rules proposed in these formalisms agree with Bayesian probability calculus in special cases but not in general. To get more reconcilement between the belief functions theory with the Bayesian probability calculus, this work proposes a new way of combining beliefs to estimate combined evidence. This approach is based on the Constraint Satisfaction Problem modeling. Thereafter, we combine all solutions of these constraint problems using Dempster's rule. This mathematical formalism is tested using information system security risk simulations. The results show that our model produces intuitive results and agrees with the Bayesian probability calculus. |
| Starting Page | 1111 |
| Ending Page | 1118 |
| File Size | 940910 |
| Page Count | 8 |
| File Format | |
| ISBN | 9786058631113 |
| e-ISBN | 9781479902842 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-07-09 |
| Publisher Place | Turkey |
| Access Restriction | Subscribed |
| Rights Holder | ISIF ( Intl Society of Information Fusi |
| Subject Keyword | Bayes methods Calculus Upper bound Mathematical model Laboratories Biological system modeling Bayesian probability calculus reconcilement Evidence theory Evidence CSP modeling Evidence combination |
| Content Type | Text |
| Resource Type | Article |
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