Results 1 to 10 of about 13,623,354 (322)
A Variation of the Algorithm to Achieve the Maximum Entropy for Belief Functions [PDF]
Entropy, 2023 Evidence theory (TE), based on imprecise probabilities, is often more appropriate than the classical theory of probability (PT) to apply in situations with inaccurate or incomplete information.
Joaquín Abellán +2 more
doaj +2 more sources
A New Correlation Measure for Belief Functions and Their Application in Data Fusion [PDF]
Entropy, 2023 Measuring the correlation between belief functions is an important issue in Dempster–Shafer theory. From the perspective of uncertainty, analyzing the correlation may provide a more comprehensive reference for uncertain information processing.
Zhuo Zhang +3 more
doaj +2 more sources
Joint Tumor Segmentation in PET-CT Images Using Co-Clustering and Fusion Based on Belief Functions. [PDF]
IEEE Trans Image Process, 2019 Precise delineation of target tumor is a key factor to ensure the effectiveness of radiation therapy. While hybrid positron emission tomography-computed tomography (PET-CT) has become a standard imaging tool in the practice of radiation oncology, many ...
Lian C, Ruan S, Denoeux T, Li H, Vera P.
europepmc +2 more sources
Decision-Making with Belief Functions: a Review [PDF]
International Journal of Approximate Reasoning, 2019 Approaches to decision-making under uncertainty in the belief function framework are reviewed. Most methods are shown to blend criteria for decision under ignorance with the maximum expected utility principle of Bayesian decision theory. A distinction is
Denoeux, Thierry
core +7 more sources
Genetic Algorithm Based on a New Similarity for Probabilistic Transformation of Belief Functions [PDF]
Entropy, 2022 Recent studies of alternative probabilistic transformation (PT) in Dempster–Shafer (DS) theory have mainly focused on investigating various schemes for assigning the mass of compound focal elements to each singleton in order to obtain a Bayesian belief ...
Yilin Dong, Lei Cao, Kezhu Zuo
doaj +2 more sources
Total belief theorem and conditional belief functions [PDF]
International Journal of Intelligent Systems, 2018 In this paper, new theoretical results for reasoning with belief functions are obtained and discussed. After a judicious decomposition of the set of focal elements of a belief function, we establish the total belief theorem (TBT).
Jean Dezert +2 more
openaire +2 more sources
Belief functions on lattices [PDF]
International Journal of Intelligent Systems, 2008 We extend the notion of belief function to the case where the underlying structure is no more the Boolean lattice of subsets of some universal set, but any lattice, which we will endow with a minimal set of properties according to our needs. We show that
Grabisch, Michel
core +10 more sources
Adaptive Belief Rule Base Modeling of Complex Industrial Systems Based on Sigmoid Functions [PDF]
EntropyIn response to the challenges posed by multifactorial nonlinear relationships and uncertainties, and to address the limitations of the existing Belief Rule Base (BRB) in nonlinear fitting, uncertainty representation, and parameter optimization, this ...
Haolan Huang +4 more
doaj +2 more sources
Application of belief functions to medical image segmentation: A review [PDF]
Information Fusion, 2022 The investigation of uncertainty is of major importance in risk-critical applications, such as medical image segmentation. Belief function theory, a formal framework for uncertainty analysis and multiple evidence fusion, has made significant ...
Ling Huang, S. Ruan
semanticscholar +1 more source
BF-QC: Belief functions on quantum circuits [PDF]
Expert systems with applications, 2021 Dempster-Shafer Theory (DST) of belief function is a basic theory of artificial intelligence, which can represent the underlying knowledge more reasonably than Probability Theory (ProbT). Because of the computation complexity exploding exponentially with
Qianli Zhou, Guojing Tian, Yong Deng
semanticscholar +1 more source