Fault diagnosis in railway track circuits using Dempster–Shafer classifier fusion

In the term of quantitative comparison of the results obtained with the proposed approach and those obtained with jointICA that has been applied to analyze

The capabilities of the proposed NN classification method based on the PW distance metric and Dempster-Shafer theory (denoted as PNN-DST) was empirically assessed through two

In this paper, we have shown that the Dempster-Shafer framework also makes it possible to evaluate and compare soft partitions produced by a wide range of methods,

The latter, however, lays bare an underlying mass function m, which has one more degree of freedom than the output probability p 1 (x). Before that, we address the multi-..

These results definitely confirm the interest of using the cautious rule, the single t-norm based rule or the two-step combination procedure introduced in this paper in a

If the belief function reference lotteries we use are Bayesian belief functions, then our representation theorem coincides with Jaffray’s representation theorem for his linear

In this study, we propose a new classifier based on Dempster-Shafer (DS) theory and deep convolutional neural networks (CNN) for set-valued classification, called the evidential

The procedure to estimate the variable of interest, denoted by q 100 , is the following: (1) from the available bivariate obser- vations of storm surges and waves, characterize