WebOct 12, 2024 · Generalized evidence theory is an extension of classical evidence theory. When belief degree of the null subset is 0, then the generalized evidence theory will be degenerated as classical Dempster-Shafer evidence theory. However, how to apply Möbius transformation to generalized evidence theory is still an open problem. WebIn everyday use, the word "theory" often means an untested hunch, or a guess without supporting evidence. But for scientists, a theory has nearly the opposite meaning. A …
The generalized maximum belief entropy model
WebMay 12, 2024 · To appropriately describe the actual situations, lots of theories have been proposed. Among them, Dempster-Shafer evidence theory is a very useful tool in managing uncertain information. To better adapt to complex situations of open world, a generalized evidence theory is designed. WebFeb 17, 2024 · 2.2 Generalized evidence theory In generalized evidence theory (GET) [ 46 ], the generalized basic probability assignment (GBPA) corresponds to BPA in Dempster–Shafer evidence theory, which can be used to model uncertain information, and the generalized combination rule (GCR) is used to combine two pieces of evidence. individual serving wine bottles
A new combination approach based on improved evidence distance
WebApr 17, 2014 · In this paper, a new theory, called as generalized evidence theory (GET), is proposed. Compared with existing methods, GET assumes that the general situation is in open world due to the uncertainty and incomplete knowledge. The conflicting evidence is handled under the framework of GET. WebSep 19, 2024 · Generalized evidence theory is an extension of D-S theory, and can express and deal with more uncertain information in the open world. In the generalized evidence theory, the strict restriction condition of m (Φ) = 0 is abandoned. It represents unknown, but not a common empty (Deng 2015 ). WebIn this paper, we propose a method under uncertain environments based on generalized evidence theory, which is used for decision making. We use K-means clustering and … lodging industry statistics