Results 11 to 20 of about 9,780 (156)
Using dempster-shafer theory to fuse multiple information sources in region-based segmentation [PDF]
, 2007 This paper presents a new method for segmentation of images into large regions that reflect the real world objects present in a scene. It explores the feasibility of utilizing spatial configuration of regions and their geometric properties (the so-called
Adamek, Tomasz, O'Connor, Noel E.
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Generalized basic probability assignments [PDF]
, 2002 Dempster-Shafer theory allows to construct belief functions from (precise) basic probability assignments. The present paper extends this idea substantially.
Augustin, Thomas
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The Dempster-Shafer Theory of Evidence [PDF]
, 2001 The Dempster-Shafer theory of evidence (here, DS theory, for brevity), sometimes called evidential reasoning (cf. Lowrance et al. [Lowrance et al., 1981]) or belief function theory, is a mechanism formalised by Shafer ([Shafer, 1976]) for representing and reasoning with uncertain, imprecise and incomplete information. It is based on Dempster’s original
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Stock portfolio selection using Dempster–Shafer evidence theory
Journal of King Saud University - Computer and Information Sciences, 2018 AbstractMarkowitz’s return–risk model for stock portfolio selection is based on the historical return data of assets. In addition to the effect of historical return, there are many other critical factors which directly or indirectly influence the stock market. We use the fuzzy Delphi method to identify the critical factors initially.
Gour Sundar Mitra Thakur +2 more
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, 1999 In this paper we extend an earlier result within Dempster-Shafer theory ["Fast Dempster-Shafer Clustering Using a Neural Network Structure," in Proc. Seventh Int. Conf. Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU'
Schubert, Johan
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Local computations in Dempster–Shafer theory of evidence
International Journal of Approximate Reasoning, 2012 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.Abstract Lithological mapping is essential for the exploration of critical minerals supporting energy transition and national defense. Although recent advancements have incorporated multi‐source data sets and leveraged machine learning and deep learning (DL) methods, lithological mapping continues to face significant challenges, such as data imbalance,
Liang Ding +3 more
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Generalized Evidence Theory [PDF]
, 2014 Conflict management is still an open issue in the application of Dempster Shafer evidence theory. A lot of works have been presented to address this issue. In this paper, a new theory, called as generalized evidence theory (GET), is proposed.
Deng, Yong
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Finding Academic Experts on a MultiSensor Approach using Shannon's Entropy
, 2013 Expert finding is an information retrieval task concerned with the search for the most knowledgeable people, in some topic, with basis on documents describing peoples activities.
Moreira, Catarina, Wichert, Andreas
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International Journal of Mechanical System Dynamics, Volume 6, Issue 1, Page 140-152, March 2026.ABSTRACT Modern engineering systems require advanced uncertainty‐aware model updating methods that address parameter correlations beyond conventional interval analysis. This paper proposes a novel framework integrating Riemannian manifold theory with Gaussian Process Regression (GPR) for systems governed by Symmetric Positive‐Definite (SPD) matrix ...
Yanhe Tao +3 more
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