This paper relates comparative belief structures and a general view of belief management in the setting of deductively closed logical representations of accepted beliefs. We show that the range of compatibility between the classical deductive closure and uncertain reasoning covers precisely the nonmonotonic 'preferential' inference system of Kraus, Lehmann and Magidor and nothing else. In terms...

The theory of structural reliability is widely applied in many fields, such as architectural design, and mechanical engineering. In this paper, the resident and the load of a structure are defined as uncertain variables and the reliability index is defined as as the uncertain measure of the event that the resident is larger than the load. Furthermore, the reliability of series and parallel stru...

A general approach to the calculation of stability radius defined in the p norm for an uncertain system with uncertain parameters q entering nonlinearly into the characteristic polynomial is presented in this paper. The stability margin problem is transformed into a standard, computationally tractable non-linear constrained optimisation problem, for which a commercial software package has been ...

Dirac measure is an important measure in many related branches to mathematics. The current paper characterizes measure-preserving transformations between two Dirac measure spaces or a Dirac measure space and a probability measure space. Also, it studies isomorphic Dirac measure spaces, equivalence Dirac measure algebras, and conjugate of Dirac measure spaces. The equivalence classes of a Dirac ...

In this paper, we proposed a hedge detection method with average perceptron, which was used in the closed challenge in CoNLL-2010 Shared Task. There are two subtasks: (1) detecting uncertain sentences and (2) identifying the in-sentence scopes of hedge cues. We use the unified learning algorithm for both subtasks since that the hedge score of sentence can be decomposed into scores of the words,...

Key indicators, such as key performance indicators or key compliance indicators are at the heart of modern business intelligence applications. Key indicators are metrics, i.e., numbers, that help an organization to measure and assess how successful it is in reaching predefined goals (e.g., lowering process execution times or increasing compliance with regulations), and typically the people look...

Methods: Since entropy is free from reliance on symmetric probability distributions and can be computed from nonmetric data, it is more general than others as a competent measure of risk. In this work, returns of securities are assumed to be uncertain variables, which cannot be estimated by randomness or fuzziness. The model in the uncertain environment is formulated as a nonlinear programming ...