In decision-making systems, how to address uncertainty plays an important role for the
improvement of system performance in uncertainty reasoning. Dempster–Shafer evidence …

Complex evidence theory (CET) is an effective method for uncertainty reasoning in
knowledge-based systems with good interpretability that has recently attracted much …

The application of multisource information fusion in real-world scenarios is an emerging
practice because it effectively uses consistent and complementary data to optimize decision …

Complex evidence theory, as a generation model of the Dempster-Shafer evidence theory,
has the ability to express uncertainty and perform uncertainty reasoning. One of the key …

Dempster-Shafer evidence theory (DST) could show its advantages during the process of
data fusion. In DST, the determination of the weight of evidence in conflict management is …

Traditional Bayesian network (BN) model is established by crisp sets and probabilities, and
its effectiveness and applicability are restricted. In order to solve this problem, a new BN …

The multi-modality characteristic of medical images calls for the application of information
fusion theory in computer aided diagnosis (CAD) algorithm design. Recently, the research of …

Abstract Dempster-Shafer theory (DST), as a generalization of Bayesian probability theory,
is a useful technique for achieving multi-source information fusion under uncertain …

How to evaluate the reliability of the information sources is a significant and open issue in
the information fusion of Dempster-Shafer evidence theory (DST). We propose a new …

Imbalanced data classification is an important research topic in real-world applications, like
fault diagnosis in an aircraft manufacturing system. The over-sampling method is often used …