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Representing Uncertainty With Information Sets | IEEE Journals & Magazine | IEEE Xplore

Representing Uncertainty With Information Sets


Abstract:

We develop new methods for the representation of uncertainty in the granularized information source values by making use of the entropy framework in the possibilistic dom...Show More

Abstract:

We develop new methods for the representation of uncertainty in the granularized information source values by making use of the entropy framework in the possibilistic domain. An information-theoretic entropy function is used to map the information source values to information (entropy) values. We term a collection of such information values as an information set. The information values are then used in an adaptive form of this entropy function to formulate Shannon transforms. A few uncertainty measures are derived from these transforms for the quantification of uncertainty. Information set is also extended to other domains, such as probabilistic, intuitionistic, and probabilistic-intuitionistic domains. A biometric application is included to demonstrate the usefulness of the study.
Published in: IEEE Transactions on Fuzzy Systems ( Volume: 24, Issue: 1, February 2016)
Page(s): 1 - 15
Date of Publication: 30 March 2015

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