Research on the approximation algorithm of the evidential theory

Zhuang Miao, Yongmei Cheng, Quan Pan, Jun Hou

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

In the Dempster-Shafer theory, the computational complexity is one of the main points of criticism this theory has to face. To solve this problem, many approximation algorithms, which always reduce the focal elements, are proposed. In this paper, a simple optimal approximation is proposed by analyzing its reasonability in quality and quantity. The genetic algorithm is applied for approximation for the first time. Then two fast algorithms, one step approximation and multi-step approximation, are proposed. As a conclusion of simulation these algorithms are better than other algorithms in accuracy and computation burden.

Original languageEnglish
Pages (from-to)187-193
Number of pages7
JournalXi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University
Volume38
Issue number2
DOIs
StatePublished - Apr 2011

Keywords

  • Approximation algorithm
  • Data fusion
  • Dempster-Shafer theory
  • Evidential theory
  • Genetic algorithm

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