Results 21 to 30 of about 75,585 (258)
Belief functions and belief maintenance in artificial intelligence
International Journal of Approximate Reasoning, 1990 The idea for this special issue first arose at the Fourth Workshop on Uncertainty in Artificial Intelligence (AI) held at Minneapolis, Minnesota, in July 1988. Jim Bezdek, the editor-in-chief of this journal, asked us if we were willing to act as guest editors.
Prakash P. Shenoy, Gautam Biswas
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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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Belief and Surprise - A Belief-Function Formulation [PDF]
, 1991 We motivate and describe a theory of belief in this paper. This theory is developed with the following view of human belief in mind. Consider the belief that an event E will occur (or has occurred or is occurring). An agent either entertains this belief or does not entertain this belief (i.e., there is no "grade" in entertaining the belief).
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Comparative Uncertainty, Belief Functions and Accepted Beliefs
CoRR, 2013 Appears in Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence (UAI1998)
Didier Dubois +2 more
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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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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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Belief functions and default reasoning
Artificial Intelligence, 2000 Appears in Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence (UAI1995)
Salem Benferhat +2 more
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RPC-EAU: Radar Plot Classification Algorithm Based on Evidence Adaptive Updating
Applied SciencesAccurately classifying targets and clutter plots is crucial in radar data processing. It is beneficial for filtering out a large amount of clutters and improving the track initiation speed and tracking accuracy of real targets.
Rui Yang, Yingbo Zhao
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