
Distance function of D numbers
DempsterShafer theory is widely applied in uncertainty modelling and kn...
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Possibilistic Networks: Parameters Learning from Imprecise Data and Evaluation strategy
There has been an everincreasing interest in multidisciplinary research...
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D numbers theory: a generalization of DempsterShafer evidence theory
Efficient modeling of uncertain information in real world is still an op...
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Modeling contaminant intrusion in water distribution networks based on D numbers
Efficient modeling on uncertain information plays an important role in e...
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Exploiting Uncertain and Temporal Information in Correlation
A modelling language is described which is suitable for the correlation ...
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Basic concepts, definitions, and methods in D number theory
As a generalization of DempsterShafer theory, D number theory (DNT) aim...
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A Generalized DempsterShafer Evidence Theory
DempsterShafer evidence theory has been widely used in various fields o...
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D numbers theory: a generalization of DempsterShafer theory
DempsterShafer theory is widely applied to uncertainty modelling and knowledge reasoning due to its ability of expressing uncertain information. However, some conditions, such as exclusiveness hypothesis and completeness constraint, limit its development and application to a large extend. To overcome these shortcomings in DempsterShafer theory and enhance its capability of representing uncertain information, a novel theory called D numbers theory is systematically proposed in this paper. Within the proposed theory, uncertain information is expressed by D numbers, reasoning and synthesization of information are implemented by D numbers combination rule. The proposed D numbers theory is an generalization of DempsterShafer theory, which inherits the advantage of DempsterShafer theory and strengthens its capability of uncertainty modelling.
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