Results 31 to 40 of about 13,623,354 (322)
Cybernetics and Information Technologies, 2015 The main purpose of this paper is to apply and to test the performance of a new method, based on belief functions, proposed by Dezert et al. in order to evaluate the quality of the individual association pairings provided in the optimal data association ...
Dezert J., Tchamova A., Konstantinova P.
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IEEE Access, 2020 The deep belief network is widely used in fault diagnosis and health management of rotating machinery. However, on the one hand, deep belief networks only tend to focus on the global information of bearing vibration, ignoring local information.
Chao Zhang +5 more
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Credibility-limited Functions for Belief Bases [PDF]
Journal of Logic and Computation, 2003 مقالة المجلة المصداقية- وظائف محدودة لأسس الاعتقاد احصل على إمكانية الوصول إدواردو فيرمي، إدواردو فيرمي ابحث عن أعمال أخرى لهذا المؤلف على: أكسفورد أكاديمي جوجل الباحث خوان ميكاليف، خوان ميكاليف ابحث عن أعمال أخرى لهذا المؤلف على: أكسفورد أكاديمي جوجل الباحث خورخي تابوادا خورخي تابوادا ابحث عن أعمال أخرى لهذا المؤلف على: أكسفورد أكاديمي جوجل الباحث ...
Eduardo Fermé +2 more
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Forecasting Using Information and Entropy Based on Belief Functions
Complexity, 2020 This paper introduces an entropy-based belief function to the forecasting problem. While the likelihood-based belief function needs to know the distribution of the objective function for the prediction, the entropy-based belief function does not. This is
Woraphon Yamaka, Songsak Sriboonchitta
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Believing Probabilistic Contents: On the Expressive Power and Coherence of Sets of Sets of Probabilities [PDF]
, 2019 Moss (2018) argues that rational agents are best thought of not as having degrees of belief in various propositions but as having beliefs in probabilistic contents, or probabilistic beliefs.
Campbell-Moore, Catrin, Konek, Jason
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A correlation coefficient of belief functions [PDF]
International Journal of Approximate Reasoning, 2016 How to manage conflict is still an open issue in Dempster–Shafer (D-S) evidence theory. The conflict coefficient k in D-S evidence theory cannot represent conflict reasonably, especially sometimes two Basic Probability Assignments (BPAs) are identical ...
Wen Jiang
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A new probability transformation method based on a correlation coefficient of belief functions
International Journal of Intelligent Systems, 2019 The Dempster‐Shafer evidence theory is widely used in many fields of information fusion because of its advantage in handling uncertain information. One of the key issues in this theory is how to make decision based on a basic probability assignment (BPA).
Wen Jiang, Chan Huang, Xinyang Deng
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Pignistic Belief Transform: A New Method of Conflict Measurement
IEEE Access, 2020 To measure conflict between two basic probability assignment functions plays the key role of conflict management in Dempster-shafer evidence theory. In this paper, a new conflict measure is proposed.
Qixuan Cai, Xiaozhuan Gao, Yong Deng
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Entropy, 2022 As well-known machine learning methods, decision trees are widely applied in classification and recognition areas. In this paper, with the uncertainty of labels handled by belief functions, a new decision tree method based on belief entropy is proposed ...
Kangkai Gao, Yong Wang, Liyao Ma
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Fuzzy logic based on Belief and Disbelief membership functions
Fuzzy Information and Engineering, 2017 Many theories are developed based on probability to deal with incomplete information. The fuzzy logic deals with belief rather than likelihood (probability). Zadeh first defined fuzzy set as a single membership function.
Poli Venkata Subba Reddy
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