(An) evidence fusion method based on the dempster-shafer theory = Dempster-shafer 이론을 이용한 징후 결합 방법

Managing uncertainty is one of the emerging issues in Expert Systems to produce high quality decisions from even incomplete and uncertain data. The Dempster-Shafer theory offers a mathematically solid framework for fusing evidence. However, its exact computation is in exponential space complexity. In order to reduce this complexity manageable, various approximation schemes have been proposed. In this thesis, we propose a new approximation scheme. That is, we extended the considering subsets to the set of given hypotheses and their complements. And, we assigned belief to be assigned to a subset A by Dempster’s combination rule, to all the smallest supersets of A in the set of considering subsets unless A is in the hypotheses set. This scheme possesses several advantages over the other approximation schemes. The first is that our scheme yields much closer approximations than others although it requires a little additional space. The second advantage is that the concept of the belief interval is still meaningful after combining evidence because the disconfirmatory belief for a proposition is available. The performance of the proposed scheme is examined through an evaluation with a sample data.
Advisors
Kim, Jin-Hyungresearcher김진형researcher
Publisher
한국과학기술원
Issue Date
1987
Identifier
65686/325007 / 000851318
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 전산학과, 1987.2, [ [ii], 35 p. ]

URI
http://hdl.handle.net/10203/33743
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=65686&flag=t
Appears in Collection
CS-Theses_Master(석사논문)
Files in This Item
There are no files associated with this item.
  • Hit : 253
  • Download : 0
  • Cited 0 times in thomson ci

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0