Results 151 to 160 of about 6,464,053 (197)

A new belief divergence measure for Dempster-Shafer theory based on belief and plausibility function and its application in multi-source data fusion

Engineering applications of artificial intelligence, 2021
Dempster–Shafer theory (DST) has extensive and important applications in information fusion. However, when the evidences are highly conflicting with each other, the Dempster’s combination rule often leads to a series of counter-intuitive results. In this
Hongfei Wang, Xinyang Deng, Wen Jiang, Jie Geng   +3 more
semanticscholar   +1 more source

Generalized combination rule for evidential reasoning approach and Dempster-Shafer theory of evidence

Information Sciences, 2021
The Dempster–Shafer (DS) theory of evidence can combine evidence with one parameter. The evidential reasoning (ER) approach is an extension of DS theory that can combine evidence with two parameters (weights and reliabilities).
Yuanwei Du, Jiaofei Zhong
semanticscholar   +1 more source

Fusion of convolutional neural networks based on Dempster–Shafer theory for automatic pneumonia detection from chest X‐ray images

International journal of imaging systems and technology (Print), 2021
Deep learning‐based applications for disease detection are essential tools for experts to effectively diagnose diseases at different stages. In this article, a new approach based on an evidence based fusion theory is proposed, allowing the combination of
Safa Ben Atitallah, Maha Driss, Wadii Boulila, A. Koubâa, H. Ghézala   +4 more
semanticscholar   +1 more source

Flood susceptibility mapping with machine learning, multi-criteria decision analysis and ensemble using Dempster Shafer Theory

, 2020
Floods are one of the most widespread natural hazards occurring across the globe. The main objective of this study was to produce flood susceptibility maps for the province of Salzburg, Austria, using two multi-criteria decision analysis (MCDA) models ...
Thimmaiah Gudiyangada Nachappa, Sepideh Tavakkoli Piralilou, Khalil Gholamnia, O. Ghorbanzadeh, Omid Rahmati, T. Blaschke   +5 more
semanticscholar   +1 more source

Deep PET/CT fusion with Dempster-Shafer theory for lymphoma segmentation

MLMI@MICCAI, 2021
Lymphoma detection and segmentation from whole-body Positron Emission Tomography/Computed Tomography (PET/CT) volumes are crucial for surgical indication and radiotherapy.
Ling Huang, T. Denoeux, D. Tonnelet, P. Decazes, S. Ruan   +4 more
semanticscholar   +1 more source

A Matrix Method of Basic Belief Assignment's Negation in Dempster–Shafer Theory

IEEE transactions on fuzzy systems, 2020
Negation is a new perspective to represent knowledge. The negation of probability distribution has been proposed, and it has a lot of interesting properties, which can reach a maximum entropy. Because of the defects of the classical probability theory in
Ziyuan Luo, Yong Deng
semanticscholar   +1 more source

An intelligent fault diagnosis approach based on Dempster-Shafer theory for hydraulic valves

Measurement, 2020
Detecting 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, Yan Ren, He-sheng Tang, Chong Shi, J. Xiang   +4 more
semanticscholar   +1 more source

A bearing fault and severity diagnostic technique using adaptive deep belief networks and Dempster–Shafer theory

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
semanticscholar   +1 more source

Fault recognition using an ensemble classifier based on Dempster-Shafer Theory

Pattern Recognition, 2020
Aiming 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, Rongxi Wang, Jianmin Gao, Zhiyong Gao, Yanjie Liang   +4 more
semanticscholar   +1 more source

Zero-sum polymatrix games with link uncertainty: A Dempster-Shafer theory solution

Applied Mathematics and Computation, 2019
Polymatrix games belong to a class of multi-player games, in which players interact pairwisely and the underlying pairwise interactions are defined by a simple undirected graph where all the edges are completely deterministic.
Xinyang Deng, Wen Jiang, Zhen Wang
semanticscholar   +1 more source