DocumentCode
2138589
Title
An uncertainty reasoning method based on evidence theory
Author
Yan He ; Caiquan Xiong ; Yifan Zhan
Author_Institution
Sch. of Comput. Sci., Hubei Univ. of Technol., Wuhan, China
fYear
2013
fDate
23-25 July 2013
Firstpage
1021
Lastpage
1025
Abstract
Uncertainty reasoning plays an important role in the inference with incomplete information. This paper presents a simplified uncertainty reasoning model based on evidence theory. This method deals with uncertain premises. A special probability assignment function is proposed to simplify the computation. A probabilistic function is presented to represents the certainty of the conclusion. We can get the probability assignment function which represents all propositions. An example is given for confirming the process of the inference. This method can deal with “ignorance” and “uncertain” information flexibly. The conclusion may be more general so that experts can present their knowledge easily.
Keywords
inference mechanisms; probability; uncertainty handling; evidence theory; ignorance factor; incomplete information; inference process; probabilistic function; probability assignment function; uncertain information; uncertainty reasoning method; Bayes methods; Cognition; Expert systems; Fuzzy reasoning; Probability distribution; Uncertainty; combination rule; evidence theory; uncertainty reasoning;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2013 Ninth International Conference on
Conference_Location
Shenyang
Type
conf
DOI
10.1109/ICNC.2013.6818126
Filename
6818126
Link To Document