A High Performance Algorithm on Uncertainty Computing

Suixiang Shi (), Qing Li, Lingyu Xu, Dengwei Xia, Xiufeng Xia and Ge Yu
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Suixiang Shi: Northeastern University, School of Information Science & Engineering
Qing Li: Shanghai University, School of Computer Science & Engineering
Lingyu Xu: Shanghai University, School of Computer Science & Engineering
Dengwei Xia: Northeastern University, School of Information Science & Engineering
Xiufeng Xia: Northeastern University, School of Information Science & Engineering
Ge Yu: Northeastern University, School of Information Science & Engineering

A chapter in Current Trends in High Performance Computing and Its Applications, 2005, pp 437-441 from Springer

Abstract: Abstract In this paper, we develop a high performance algorithm which is adapted to uncertainty computing and give a new combination rules coming from the D–S and supply a gap that Dempster ignoranced. The evidence sources are adapted in different cases. The credibility of the evidence changes along with the different focus element. So, we give various credibility for every focus element to increase precision. The new method improves the precision and gets rid of disconvergent answer.

Keywords: uncertainty computing; information fusion; Dempster-Shafer; evidence; theory; credibility (search for similar items in EconPapers)
Date: 2005
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-540-27912-9_58

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DOI: 10.1007/3-540-27912-1_58

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