A Mathematical Approach to Represent Uncertain Data using Evidence and Possibility Theory

Authors

  • Madhavi Kolukuluri JNTUK University College of Engineering Vizianagaram, India
  • P. E. S. N. Krishna Prasad Prasad V. Potluri Siddhartha Institute of Technology, Vijayawada, India
  • B. D. C. N. Prasad Prasad V. Potluri Siddhartha Institute of Technology, Vijayawada, India

DOI:

https://doi.org/10.37591/rrdms.v1i1.88

Keywords:

Uncertainty, fuzzy measures, evidence theory, belief measure, plausibility measure, possibility measure, necessity measure, dumpster’s combination

Abstract

The uncertainty involved in any problem solving situation is a result of some information deficiency. Information may be incomplete, in precise, not fully reliable, and contradictory. In general, the lack of information may result in different types of uncertainty. In this paper we discuss the statistical approach for representing uncertain data using evidence theory and possibility theory and applications to the evidence and possibility approximation problems are briefly presented.

References

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George J.Klir, Bo Yuan .Fuzzy Sets and Fuzzy Lozic Theory and Applications.

Glenn Shafer. A Mathematical Theory Of Evidence, Princeton University Press.1976.

Klir, G. J. Developments in uncertainty-based information.. In:Yovits, M.C., ed., Advances in computers. Academic press, San Diego.1993.

Wang, P. P. et al.[1983], Advances in Fuzzy Theory and Technology, Vol.I. Bookwrights Press, Durham,NC.1983; 1.

Zadeh, L.A. Fuzzy sets as a basis for a theory of possibility.Fuzzy Sets and Systems.

Dempster A. P. Upper and lower probability inferences based on a sample from a finite univariate population. Biometrika; 54 (1967):515–528p.

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Published

2014-05-08

Issue

Vol. 1 No. 1 (2014)

Section

Research Articles

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