Name
Abstract | ||
|---|---|---|
Mass assignment theory techniques for processing uncertainty in Fril are reviewed. The notion of the probability of a fuzzy event is introduced together with the t-norm definition of conditional probabilities. The latter is then shown to be probability/possibility inconsistent. An alternative theory of conditional probabilities based on mass assignments is presented together with a number of results illustrating some intuitive properties. In particular, the mass assignment theory of conditional probabilities is shown to be probability/possibility consistent. |
Year | DOI | Venue |
|---|---|---|
1996 | 10.1016/0165-0114(95)00297-9 | Fuzzy Sets and Systems |
Keywords | Field | DocType |
voting model,mass assignment,mass assignment theory,probability of a fuzzy event,semantic unification,fuzzy event,possibility measure,conditional probability | Discrete mathematics,Conditional probability distribution,Conditional probability,Tree diagram,Posterior probability,Regular conditional probability,Artificial intelligence,Chain rule (probability),Conditional mutual information,Law of total probability,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
83 | 3 | Fuzzy Sets and Systems |
Citations | PageRank | References |
60 | 4.28 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| J. F. Baldwin | 1 | 66 | 5.00 |
| Jonathan Lawry | 2 | 172 | 19.06 |
| T. P. Martin | 3 | 75 | 6.33 |