Using Non-Subjective Approximation Algorithm of D-S Evidence Theory for Improving Data Fusion
نویسندگان
چکیده
منابع مشابه
Improving D-S Evidence Theory for Data Fusion System
Dempster-Shafer evidence theory is an efficient method to process uncertain, incomplete and vague information in data fusion. The combination of conflicting bodies of evidence has been one of the most important issues in Dempster-Shafer evidence theory since the example of counter-intuitive results produced by Dempster’s rule was found. Based on the framework of the Dempster-Shafer evidence the...
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Conventional D-S evidence theory has an unavoidable disadvantage in that it will give counter-intuitive result when fusing high conflict information. This paper proposes an improved method to solve this problem. By reassigning weight factors before fusing, the method can give reasonable results especially when the initial weight factors of conflict evidences are almost equal. It gives an adjust...
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15 صفحه اولD-S Theory Based on an Improved PSO for Data Fusion
The Dempster-Shafer (D-S) theory is an excellent method of information fusion. Because of the difference which is caused by the sensors, it is essential to deal with the evidence with a method of weighed D-S theory. The new method to deal with data fusion based on improved D-S theory has been proposed, and set up the concept of weight of sensor evidence itself and evidence distance based on a q...
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ژورنال
عنوان ژورنال: International Journal of Performability Engineering
سال: 2019
ISSN: 0973-1318
DOI: 10.23940/ijpe.19.10.p15.26922700