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Uncertain data has been emerged as an important problem in database systems due to the imprecise nature of many applications. To handle the uncertainty, probabilistic databases can be used to store uncertain data, and querying facilities are provided to yield answers with confidence. However, the uncertainty may propagate, hence the returned results from a query or mining process may not be useful...
Classical reliability theory always uses probability theory to quantify uncertainty information and it will meet a lot of difficulties when data is sparse or quantification of uncertainty is based on subjective information. As a generalization of probability theory, imprecise probability theory can express subjective information on a behavioral interpretation via the buying and selling price for a...
As the end point of the power system, a distribution system directly connects with the consumers. The reliability of power supply is directly related with consumers. However, uncertainty of the original parameters of components may be caused by lacking of statistical information and the statistic error. It will inevitably produce large errors if we directly use these parameters for evaluation. The...
Dempster-Shafer (DS) theory provides a solution to fuse multisensor data, which are presented in a hypothesis space comprising mutually exclusive and exhaustive propositions and their unions. The fusion result is a description of the proposition with the values of support, plausibility, and uncertainty interval. However, in some applications, numerical values of a continuous function, instead of a...
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