Open AccessPosted Content
Fractal-based belief entropy.
Qianli Zhou,Yong Deng +1 more
TLDR
Simulates the pignistic probability transformation (PPT) process based on the idea of fractal, making the PPT process and the information volume lost during transformation more intuitive, and proposes a new belief entropy called Fractal-based (FB) entropy, which is the first time to apply fractal idea in belief entropy.Abstract:
The total uncertainty measurement of basic probability assignment (BPA) in evidence theory has always been an open issue. Although many scholars have put forward various measures and requirements of bodies of evidence (BoE), none of them are widely recognized. So in order to express the uncertainty in evidence theory, transforming basic probability assignment (BPA) into probability distribution is a widely used method, but all the previous methods of probability transformation are directly allocating focal elements in evidence theory to their elements without specific transformation process. Based on above, this paper simulates the pignistic probability transformation (PPT) process based on the idea of fractal, making the PPT process and the information volume lost during transformation more intuitive. Then apply this idea to the total uncertainty measure in evidence theory. A new belief entropy called Fractal-based (FB) entropy is proposed, which is the first time to apply fractal idea in belief entropy. After verification, the new entropy is superior to all existing total uncertainty measurements.read more
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Posted Content
A Method for Recognizing Fatigue Driving Based on Dempster-Shafer Theory and Fuzzy Neural Network
TL;DR: Experimental results demonstrate that the recognition method proposed in this paper can obtain reasonable results with the combination of information given by multiple features and can also effectively and accurately describe driving states.
Journal ArticleDOI
Measuring Uncertainty in the Negation Evidence for Multi-Source Information Fusion
TL;DR: Wang et al. as discussed by the authors proposed a method of measuring the uncertainty in negation evidence based on the negation function of BPA and improved the multi-source information fusion considering uncertainty quantification in the negative evidence with the new measure.
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Higher order information volume of mass function.
Qianli Zhou,Yong Deng +1 more
TL;DR: This paper gives Deng entropy a new explanation based on the fractal idea, and proposed its generalization called time fractal-based (TFB) entropy, which can express more uncertain information than all of existing methods.
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A New Non-Specificity Measure in Evidence Theory Based on Belief Intervals
Yang Yi,Han Deqiang,Jean Dezert +2 more
TL;DR: In the theory based on belief functions, the measure of uncertainty is an important concept, which is used for representing some types of uncertainty incorporated in bodies of evidence such as the discord and the non-specificity as mentioned in this paper.
Journal Article
A new distance-based total uncertainty measure in the theory of belief functions
YangYi,HanDeqiang +1 more
TL;DR: A new total uncertainty measure in evidence theory is proposed, directly defined in the evidential framework and not a generalization of those in the probabilistic framework.
References
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Book
Fuzzy sets
TL;DR: A separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
Book
A mathematical theory of evidence
TL;DR: This book develops an alternative to the additive set functions and the rule of conditioning of the Bayesian theory: set functions that need only be what Choquet called "monotone of order of infinity." and Dempster's rule for combining such set functions.
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The Mathematical Theory of Communication
TL;DR: The Mathematical Theory of Communication (MTOC) as discussed by the authors was originally published as a paper on communication theory more than fifty years ago and has since gone through four hardcover and sixteen paperback printings.
Upper and Lower Probabilities Induced by a Multivalued Mapping.
TL;DR: In this paper, a multivalued mapping from a space X to a space S carries a probability measure defined over subsets of X into a system of upper and lower probabilities over S. Some basic properties of such systems are explored in Sects. 1 and 2.
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A New Belief Entropy to Measure Uncertainty of Basic Probability Assignments Based on Belief Function and Plausibility Function.
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