Results 191 to 200 of about 16,307 (244)

Lamb Wave-Based Damage Fusion Detection of Composite Laminate Panels Using Distance Analysis and Evidence Theory. [PDF]

Sensors (Basel)
Wang L, Liu G, Wang X, Yang Y.
europepmc   +1 more source

Permittivity Measurement in Multi-Phase Heterogeneous Concrete Using Evidential Regression Deep Network and High-Frequency Electromagnetic Waves. [PDF]

Materials (Basel)
Hou Z, Liu H, Cheng J, Zhang Q, Tong Z.
europepmc   +1 more source

Data-driven Bayesian networks for risk scenario mapping of Falls from height accidents. [PDF]

PLoS One
Li J, Wang T.
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Dempster-Shafer Theory for Stock Selection

2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC), 2021
The Dempster-Shafer theory is used to develop a stock selection method. Monte Carlo algorithms are employed to approximate Dempster’s combination rule to overcome the high computational complexity of the method. Numerical results are obtained to compare the proposed method with another Dempster-Shafer based stock selection method and the S&P 500 ...
Nima Salehy, Giray Ökten
openaire   +1 more source

A clash in Dempster-Shafer theory

10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297), 2005
In this paper, we justify Dempster's rule of combination under Shafer's interpretation of belief functions. Then, we argue that there is a clash in Dempster-Shafer (D-S) theory. That is, the definition which Shafer gives for belief function Bel/sub /spl infin// is not consistent with his interpretation for the belief function.
Wei Xiong, Xudong Luo, Shier Ju
openaire   +1 more source

MODELLING DEPENDENCE IN DEMPSTER-SHAFER THEORY

International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2007
Belief functions can only be combined by Dempster's rule when they are based on independent items of evidence. This paper proposes a method for handling the case where there is some probabilistic dependence among the items of evidence. The method relies on compact representations of joint probability distributions on the assumption variables associated
Paul-André Monney, Moses W. Chan
openaire   +1 more source

Measures of discord in the Dempster-Shafer theory

Information Sciences, 1993
This paper presents a complementary study of a previous one of the authors [Int. J. Gen. Syst. 18, No. 2, 155-166 (1990; Zbl 0732.60004)] in which a measure of discord was introduced as an uncertainty measure in the framework of Dempster-Shafer theory. That measure overcomes certain deficiencies in two measures defined in the same context, the measure ...
Arthur Ramer, George J. Klir
openaire   +1 more source

An extended approach for Dempster-Shafer theory

Proceedings Fifth IEEE Workshop on Mobile Computing Systems and Applications, 2004
The modeling of epitesmic knowledge is a necessity of most systems dealing with some sort of artificial reasoning. There are several formalisms able to mathematically model someone's degrees of belief. A very popular one is the Bayesian theory, which is based on a prior knowledge of a probability distribution.
Fabio Campos, Sérgio Cavalcante
openaire   +1 more source

Dempster-Shafer theory for image restoration

Proceedings of the International Conference and Workshop on Emerging Trends in Technology, 2010
This work proposes a new filter based on progressive decision using Dempster-Shafer theory, to suppress the impulse noise to preserve details of image and to restore image corrupted by random valued impulse noise. The new filter mechanism is composed of an efficient D-S impulse detector and a noise filter. The D-S evidence theory provides a way to deal
R. K. Kulkarni, Sukadev Meher, V. S. Lunge   +2 more
openaire   +1 more source