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MODELLING DEPENDENCE IN DEMPSTER-SHAFER THEORY
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2007Belief functions can only be combined by Dempster's rule when they are based on independent items of evidence. This paper proposes a method for handling the case where there is some probabilistic dependence among the items of evidence. The method relies on compact representations of joint probability distributions on the assumption variables associated
Monney, Paul-Andre, Chan, Moses
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Geospatial Modeling Using Dempster–Shafer Theory
IEEE Transactions on Cybernetics, 2017Uncertainty in spatial geometrical issues is represented using Dempster-Shafer (D-S) theory. Interval approaches are used for D-S uncertainty of spatial locations and the associated arithmetic operations on such intervals described. Categories of uncertainty for points and lines are defined using interval formulations.
Paul A, Elmore +2 more
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An intelligent fault diagnosis approach based on Dempster-Shafer theory for hydraulic valves
Measurement, 2020Detecting faults in hydraulic valves are of significance to improve the reliability and security of hydraulic systems. However, it is difficult to detect multiple faults in hydraulic valves using existing approaches due to closed structural components ...
Xiancheng Ji +4 more
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Discovering user preferences using Dempster–Shafer theory
Fuzzy Sets and Systems, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Troiano L +2 more
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1984
This is a theory of evidence potentially suitable for knowledge-based systems. The system is based on “basic probabilities” which can be visualized as probability masses that are constrained to stay within the subset with which they are associated, but are free to move over every point in the subset.
Alan Bundy, Lincoln Wallen
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This is a theory of evidence potentially suitable for knowledge-based systems. The system is based on “basic probabilities” which can be visualized as probability masses that are constrained to stay within the subset with which they are associated, but are free to move over every point in the subset.
Alan Bundy, Lincoln Wallen
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Structural Health Monitoring, 2020
An artificial intelligent bearing fault and hierarchical severity diagnosis framework is proposed in this study. The framework utilizes a combined deep belief networks (DBNs) and Dempster–Shafer (D-S) theory fault diagnosis scheme and adopts a two-stage ...
Kun Yu, T. Lin, Jiwen Tan
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An artificial intelligent bearing fault and hierarchical severity diagnosis framework is proposed in this study. The framework utilizes a combined deep belief networks (DBNs) and Dempster–Shafer (D-S) theory fault diagnosis scheme and adopts a two-stage ...
Kun Yu, T. Lin, Jiwen Tan
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PRECISE EYE LOCATION USING DEMPSTER–SHAFER THEORY
International Journal of Wavelets, Multiresolution and Information Processing, 2007Eye location is an important step in automatic visual interpretation and face recognition. In this paper, we present a novel eye location algorithm based on Dempster–Shafer's evidential reasoning. Four eye detectors are trained by AdaBoost with different combinations of feature spaces and samples. They detect face region respectively and produce an eye
Gao, Yong, Wang, Yangsheng
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Symbolic Dempster-Shafer Theory
Journal of Computer Research and Development, 2005采用一个全序的符号值集合来代替数值信任度集合[0,1],提出定性Dempster-Shfer理论来处理既有不确定性又有不精确性的推理问题.首先,定义了适合对不确定性进行定性表达和推理的定性mass函数、定性信任函数等概念,并且研究了这些概念之间的基本关系;其次,详细讨论了定性证据合成问题,提出了基于平均策略的证据合成规则.这种定性Dempster-Shfer理论与其他相关理论相比,既通过在定性领域重新定义Dempster-Shfer理论的基本概念,继承了Dempster-Shfer理论在不确定推理方面的主要特点,同时又具有适合对不精确性操作的既有严格定义又符合直观特性的定性算子,因此更适合基于Dempster-Shafer理论框架不精确表示和处理不确定性.
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Shape from silhouette using Dempster–Shafer theory
Pattern Recognition, 2010zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Díaz-Más, L. +3 more
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Fault recognition using an ensemble classifier based on Dempster-Shafer Theory
Pattern Recognition, 2020Aiming at the poor performance of individual classifier in the field of fault recognition, in this paper, a new ensemble classifier is constructed to improve the classification accuracy by combining multiple classifiers based on Dempster–Shafer Theory ...
Zhen Wang +4 more
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