In Dempster-Shafer (DS) theory, multiple information from the distinct information sources are combined to obtain a single Basic Probability Assignment (BPA) function. The well-known combination rule of Dempster-Shafer (DS) provides the weaker solution to the management of conflicting information at the normalization stage. Even this rule fails and provide the counter intuitive results while co...

The power transformer is one of the most critical and expensive components for the stable operation of the power system. Hence, how to obtain the health condition of transformer is of great importance for power utilities. Multi-attribute decision-making (MADM), due to its ability of solving multi-source information problems, has become a quite effective tool to evaluate the health condition of ...

Shafer and Vovk have shown how to base probability theory on game theory. In this framework, we give probabilities an empirical predictive meaning by means of a form Cournot's principle, which says that reality will not permit gambler win disproportionately the capital he risks. How does principle apply causal interpretation graphical models?

This study presents a framework for calculating the risk of various projects, especially projects under uncertain circumstances. First, the related literature is reviewed and then the relationship between risk and projects is examined. Using a case study an approach is provided to determine the project risk in uncertain circumstances where sufficient data is not available for decision-making. I...

We propose a new classifier based on Dempster-Shafer (DS) theory and convolutional neural network (CNN) architecture for set-valued classification. In this classifier, called the evidential deep-learning pooling layers first extract high-dimensional features from input data. The are then converted into mass functions aggregated by Dempster’s rule in DS layer. Finally, an expected utility layer ...