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June 2016
Manish Aggarwal

Manish Aggarwal is a faculty in Information Systems area.  His areas of research interest include Information Systems, Decision Sciences, Soft Computing, Fuzzy Systems, Knowledge Representation under Uncertainty, Machine Learning, Artificial Intelligence
Abstracts of other articles published in refereed journals included in this issue
  • Representing Uncertainty with Information Sets
    In IEEE Transactions on Fuzzy Systems, 24(1), February 2016, 1-15(Online Reference: 10.1109/TFUZZ.2015.2417593)

    Manish Aggarwal and Madasu Hanmandlu

    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.

Abstracts of other articles published in refereed journals included in this issue

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