We propose a new definition of entropy for basic probability assignments (BPA) in the Dempster-Shafer (D-S) theory of belief functions, which is interpreted as a measure of total uncertainty in the BPA. Our definition is different from the definitions proposed by H¨ohle, Smets, Yager, Nguyen, Dubois-Prade, Lamata-Moral, Klir-Ramer, Klir-Parviz, Pal et al., MaedaIchihashi, Harmanec-Klir, Jousselme et al., and Pouly et al. We state a list of five desired properties of entropy for D-S belief functions theory that are motivated by Shannon’s definition of entropy for probability functions together with the requirement that any definition should be consistent with the semantics of D-S belief functions theory
The aim of this paper is to define global measures of uncertainty in the framework of Dempster-Shafe...
The Dempster-Shafer theory of evidence (DS theory) is one of the major approaches for reasoning unde...
Dempster-Shafer theory allows to construct belief functions from (precise) basic probability assignm...
We propose a new definition of entropy for basic probability assignments (BPA) in the Dempster-Shafe...
We propose a new definition of entropy of basic probability assignments (BPAs) in the Dempster–Shafe...
We propose a new definition of entropy of basic probability assignments (BPAs) in the Dempster–Shafe...
How to quantify the uncertain information in the framework of Dempster-Shafer evidence theory is sti...
In Dempster-Shafer Theory (DST) of evidencee and transferable belief model (TBM), the probability tr...
The Dempster-Shafer theory (DST) is an information fusion framework and widely used in many fields. ...
Since the Dempster-Shafer evidence theory was developed, it has been extensively concerned by resear...
In 2018, Jiroušek and Shenoy proposed a definition of entropy for Dempster-Shafer (D-S) belief funct...
By analyzing the relationships among chance, weight of evidence and degree of belief, it is shown t...
The elementary notions and relations of the so called Dempster-Shafer theory, introducing belief fun...
Dempster Shafer evidence theory has widely used in many applications due to its advantages to handle...
Shannnon entropy is an efficient tool to measure uncertain information. However, it cannot handle th...
The aim of this paper is to define global measures of uncertainty in the framework of Dempster-Shafe...
The Dempster-Shafer theory of evidence (DS theory) is one of the major approaches for reasoning unde...
Dempster-Shafer theory allows to construct belief functions from (precise) basic probability assignm...
We propose a new definition of entropy for basic probability assignments (BPA) in the Dempster-Shafe...
We propose a new definition of entropy of basic probability assignments (BPAs) in the Dempster–Shafe...
We propose a new definition of entropy of basic probability assignments (BPAs) in the Dempster–Shafe...
How to quantify the uncertain information in the framework of Dempster-Shafer evidence theory is sti...
In Dempster-Shafer Theory (DST) of evidencee and transferable belief model (TBM), the probability tr...
The Dempster-Shafer theory (DST) is an information fusion framework and widely used in many fields. ...
Since the Dempster-Shafer evidence theory was developed, it has been extensively concerned by resear...
In 2018, Jiroušek and Shenoy proposed a definition of entropy for Dempster-Shafer (D-S) belief funct...
By analyzing the relationships among chance, weight of evidence and degree of belief, it is shown t...
The elementary notions and relations of the so called Dempster-Shafer theory, introducing belief fun...
Dempster Shafer evidence theory has widely used in many applications due to its advantages to handle...
Shannnon entropy is an efficient tool to measure uncertain information. However, it cannot handle th...
The aim of this paper is to define global measures of uncertainty in the framework of Dempster-Shafe...
The Dempster-Shafer theory of evidence (DS theory) is one of the major approaches for reasoning unde...
Dempster-Shafer theory allows to construct belief functions from (precise) basic probability assignm...