Parameter estimation based on interval-valued belief structures

Xinyang Deng, Yong Hu, Tung Sun Chan, Sankaran Mahadevan, Yong Deng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

9 Citations (Scopus)

Abstract

Parameter estimation based on uncertain data represented as belief structures is one of the latest problems in the Dempster-Shafer theory. In this paper, a novel method is proposed for the parameter estimation in the case where belief structures are uncertain and represented as interval-valued belief structures. Within our proposed method, the maximization of likelihood criterion and minimization of estimated parameter's uncertainty are taken into consideration simultaneously. As an illustration, the proposed method is employed to estimate parameters for deterministic and uncertain belief structures, which demonstrates its effectiveness and versatility.
Original languageEnglish
Pages (from-to)579-582
Number of pages4
JournalEuropean Journal of Operational Research
Volume241
Issue number2
DOIs
Publication statusPublished - 1 Jan 2015

Keywords

  • Belief function
  • Dempster-Shafer theory
  • Interval-valued belief structures
  • Maximum likelihood estimation
  • Parameter estimation

ASJC Scopus subject areas

  • Modelling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

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