Shannnon entropy is an efficient tool to measure uncertain information. However, it cannot handle the more uncertain situation when the uncertainty is represented by basic probability assignment (BPA), instead of probability distribution, under the framework of Dempster Shafer evidence theory. To address this issue, a new entropy, named as Deng entropy, is proposed
The aim of this paper is to define global measures of uncertainty in the framework of Dempster-Shafe...
The Dempster-Shafer theory (DST) is an information fusion framework and widely used in many fields. ...
We discuss pragmatic information measures (hypergraph entropy and fractional entropy) inspired by so...
Shannnon entropy is an efficient tool to measure uncertain information. How-ever, it cannot handle t...
Dempster Shafer evidence theory has widely used in many applications due to its advantages to handle...
How to quantify the uncertain information in the framework of Dempster-Shafer evidence theory is sti...
The extropy has recently been introduced as the dual concept of entropy. Moreover, in the context of...
The extropy has recently been introduced as the dual concept of entropy. Moreover, in the context of...
Quantification of uncertain degree in the Dempster-Shafer evidence theory (DST) framework with belie...
Since the Dempster-Shafer evidence theory was developed, it has been extensively concerned by resear...
Quantification of uncertain degree in the Dempster-Shafer evidence theory (DST) framework with belie...
Deng entropy and extropy are two measures useful in the Dempster–Shafer evidence theory (DST) to stu...
Deng entropy and extropy are two measures useful in the Dempster–Shafer evidence theory (DST) to stu...
PPascal triangle (known as Yang Hui Triangle in Chinese) is an important model in mathematics while ...
Given a probability distribution, its corresponding information volume is Shannon entropy. However, ...
The aim of this paper is to define global measures of uncertainty in the framework of Dempster-Shafe...
The Dempster-Shafer theory (DST) is an information fusion framework and widely used in many fields. ...
We discuss pragmatic information measures (hypergraph entropy and fractional entropy) inspired by so...
Shannnon entropy is an efficient tool to measure uncertain information. How-ever, it cannot handle t...
Dempster Shafer evidence theory has widely used in many applications due to its advantages to handle...
How to quantify the uncertain information in the framework of Dempster-Shafer evidence theory is sti...
The extropy has recently been introduced as the dual concept of entropy. Moreover, in the context of...
The extropy has recently been introduced as the dual concept of entropy. Moreover, in the context of...
Quantification of uncertain degree in the Dempster-Shafer evidence theory (DST) framework with belie...
Since the Dempster-Shafer evidence theory was developed, it has been extensively concerned by resear...
Quantification of uncertain degree in the Dempster-Shafer evidence theory (DST) framework with belie...
Deng entropy and extropy are two measures useful in the Dempster–Shafer evidence theory (DST) to stu...
Deng entropy and extropy are two measures useful in the Dempster–Shafer evidence theory (DST) to stu...
PPascal triangle (known as Yang Hui Triangle in Chinese) is an important model in mathematics while ...
Given a probability distribution, its corresponding information volume is Shannon entropy. However, ...
The aim of this paper is to define global measures of uncertainty in the framework of Dempster-Shafe...
The Dempster-Shafer theory (DST) is an information fusion framework and widely used in many fields. ...
We discuss pragmatic information measures (hypergraph entropy and fractional entropy) inspired by so...
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