SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Extended k-Nearest Neighbours based on Evidence Theory
8 references·0 citing·30 second hop
Extended k-Nearest Neighbours based on Evidence Theory (2004)Extended k-Nearest Neighbours based on Ev…A Framework for Evidential-Reasoning Systems (2008)A Framework for Evidential-Re…Approximating the combination of belief functions using the fast Möbius transform in a coarsened frame (2002)Approximating the combination…INNER AND OUTER APPROXIMATION OF BELIEF STRUCTURES USING A HIERARCHICAL CLUSTERING APPROACH (2001)INNER AND OUTER APPROXIMATION…Algorithms for Dempster-Shafer Theory (2000)Algorithms for Dempster-Shafe…An evidence-theoretic k-NN rule with parameter optimization (1998)An evidence-theoretic k-NN ru…Approximation algorithms and decision making in the Dempster-Shafer theory of evidence — An empirical study (1997)Approximation algorithms and …Approximations for efficient computation in the theory of evidence (1993)Approximations for efficient …The combination of evidence in the transferable belief model (1990)The combination of evidence i…Constructing the Pignistic Probability Function in a Context of Uncertainty (1990)Advances in the Dempster-Shafer theory of evidence (1994)Evidential reasoning in large partially ordered sets (2011)Distributed combination of belief functions (2020)Fuzzy Sets and Systems - Theory and Applications (1980)Judgment under Uncertainty (1982)Judgment under uncertainty: Causality and attribution (1982)k-order additive discrete fuzzy measures and their representation (1997)A new distance between two bodies of evidence (2001)Evidential reasoning rule for evidence combination (2013)Fuzzy sets (1965)A method for managing evidential reasoning in a hierarchical hypothesis space (1985)Computational Methods for A Mathematical Theory of Evidence (2008)A mathematical theory of evidence (1977)Combination of Evidence in Dempster-Shafer Theory (2002)The evidential reasoning approach for MADA under both probabilistic and fuzzy uncertainties (2004)Representation and combination of uncertainty with belief functions and possibility measures (1988)Uncertainty-Based Information: Elements of Generalized Information Theory (1998)Risk assessment based on weak information using belief functions: a case study in water treatment (2006)On the relative belief transform (2012)Ruin Time of Uncertain Insurance Risk Process (2016)A k-nearest neighbor classification rule based on Dempster-Shafer theory (1995)Resource bounded and anytime approximation of belief function computations (2002)A k-Nearest Neighbor Classification Rule Based on Dempster-Shafer Theory (2008)Analysis of fuzzy information (1987)Decision analysis using belief functions (1990)The Dempster–Shafer theory of evidence: an alternative approach to multicriteria decision modelling (2000)Classic Works of the Dempster-Shafer Theory of Belief Functions (2008)A neural network classifier based on Dempster-Shafer theory (2000)Conjunctive and disjunctive combination of belief functions induced by nondistinct bodies of evidence (2007)
this work references cited by second hop

References

  • 1990The combination of evidence in the transferable belief model1,113 cited
  • 1998An evidence-theoretic k-NN rule with parameter optimization310 cited
  • 1993Approximations for efficient computation in the theory of evidence226 cited
  • 1997Approximation algorithms and decision making in the Dempster-Shafer theory of evidence — An empirical study177 cited
  • 2008A Framework for Evidential-Reasoning Systems172 cited
  • 2001INNER AND OUTER APPROXIMATION OF BELIEF STRUCTURES USING A HIERARCHICAL CLUSTERING APPROACH89 cited
  • 2000Algorithms for Dempster-Shafer Theory79 cited
  • 2002Approximating the combination of belief functions using the fast Möbius transform in a coarsened frame71 cited

Cited by

No citing works inside the corpus for this window.

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work