dc.contributor.author | Aggarwal, Manish | |
dc.contributor.author | Hanmandlu, M. | |
dc.date.accessioned | 2017-06-22T04:35:59Z | |
dc.date.available | 2017-06-22T04:35:59Z | |
dc.date.issued | 2016 | |
dc.identifier.citation | Aggarwal M., Hanmandlu M. (2016). Representing uncertainty with information sets. IEEE Transactions on Fuzzy Systems, 24(1), 1-15. | en_US |
dc.identifier.uri | http://hdl.handle.net/11718/19429 | |
dc.description.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. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
dc.subject | Agent | en_US |
dc.subject | Fuzzy sets | en_US |
dc.subject | Hanman-Anirban entropy function; information sets | en_US |
dc.subject | Information source | en_US |
dc.subject | Intuitionistic information set; | en_US |
dc.subject | Probabilistic information set | en_US |
dc.subject | Shannon transforms | en_US |
dc.subject | Uncertainty measures | en_US |
dc.title | Representing uncertainty with information sets | en_US |
dc.type | Article | en_US |