NDLI: Study on algorithms of determining basic probability assignment function in Dempster-Shafer evidence theory

Content Provider	IEEE Xplore Digital Library
Author	Xin Guan Xiao Yi You He
Copyright Year	2008
Description	Author affiliation: Res. Inst. of Inf. Fusion, Naval Aeronaut. & Astronaut. Univ., Yantai (Xin Guan; Xiao Yi; You He)
Abstract	Dempster-Shafer evidence theory (D-S theory) provides a useful computational scheme for integrating uncertainty information from multiple sources in artificial intelligence systems. D-S evidence theory is a useful method for dealing with uncertainty problems. Therefore, it has been successfully applied in data fusion and pattern recognition. However, it also has some shortcomings. The key problem to D-S reasoning is basic probability assignment (BPA) function, which to a great extent limits its applications. To solve this problem, this paper presents three methods to constructing the BPA function. These methods are based on gray correlation analysis, fuzzy sets, and attribute measure respectively. Furthermore, experiments of recognizing the emitter purpose are selected to demonstrate these methods of determining the BPA function proposed. Experimental results show that the performance of these new methods is accurate and effective.
Starting Page	121
Ending Page	126
File Size	382523
Page Count	6
File Format	PDF
ISBN	9781424420957
DOI	10.1109/ICMLC.2008.4620390
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-07-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Correlation Indexes Pattern recognition Arrays Machine learning Cybernetics Training data Dempster-Shafer evidence theory Basic probability assignment function Gray correlation analysis Fuzzy set Attribute measure
Content Type	Text
Resource Type	Article

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