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 :
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