A belief Sharma-Mittal divergence with its application in multi-sensor information fusion

Lyu, Shen; Liu, Zhe

doi:10.1007/s40314-023-02542-0

Cited by 10 publications

(2 citation statements)

References 42 publications

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“…To measure uncertainty of a given system, several methods and entropies have been proposed, including χ entropy (Xiao, 2021b) for the complex-valued distribution, belief structure method (Cui et al, 2022) for physiological signals, betweenness structural entropy (Zhang and Li, 2022) and local structure entropy (Lei and Cheong, 2022b) for complex networks, an improved belief entropy (Chen and Deng, 2023b) and divergence method (Gao and Xiao, 2022;Lyu and Liu, 2024) for decision making, generalized weighted permutation entropy for biomes analysis (Stosic et al, 2022;Stosic and Stosic, 2024). Some methods, such as the Deng entropy (Deng, 2016), though have been subject to critique (Abellán, 2017;Moral-García and Abellán, 2020), continue to be widely used in many areas and theories, including multi-criteria decision-making (Xiao, 2020), information fusion (Xiao, 2021a(Xiao, , 2022a, pattern recognition (Kazemi et al, 2021), decisions prediction and evaluation (Lai and Cheong, 2022a), fractal dimension analysis (Qiang et al, 2022), information dimension analysis (Lei, 2022), and prior distribution (Li and Xiao, 2023).…”

Section: Deng Entropymentioning

confidence: 99%

International Comparison on the Application of Information Technology in High School Mathematics Textbooks

Zhou

2021

School Mathematics Textbooks in China

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Ultra-dense networks are widely regarded as a promising solution to explosively growing applications of Internet-of-Things (IoT) mobile devices (IMDs). However, complicated and severe interferences need to be tackled properly in such networks. To this end, both orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) are utilized at first. Then, in order to attain a goal of green and secure computation offloading, under the proportional allocation of computational resources and the constraints of latency and security cost, joint device association, channel selection, security service assignment, power control and computation offloading are done for minimizing the overall energy consumed by all IMDs. It is noteworthy that multi-step computation offloading is concentrated to balance the network loads and utilize computing resources fully. Since the finally formulated problem is in a nonlinear mixed-integer form, it may be very difficult to find its closed-form solution. To solve it, an improved whale optimization algorithm (IWOA) is designed. As for this algorithm, the convergence, computational complexity and parallel implementation are analyzed in detail. Simulation results show that the designed algorithm may achieve lower energy consumption than other existing algorithms under the constraints of latency and security cost.

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Section: Deng Entropymentioning

confidence: 99%

International Comparison on the Application of Information Technology in High School Mathematics Textbooks

Zhou

2021

School Mathematics Textbooks in China

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“…Among them, Dempster-Shafer evidence theory (DSET) [20], as a powerful tool for modeling uncertain and imprecise information, which has been successfully applied in pattern recognition [21][22][23], fault diagnosis [24,25], information fusion [26,27] and image analysis [28,29]. DSET provides a richer representation of uncertainty by allowing belief values to be assigned to sets of propositions, rather than just individual events [15].…”

Section: Introductionmentioning

confidence: 99%

A Belief Similarity Measure for Dempster-Shafer Evidence Theory and Application in Decision Making

Liu

2024

J. Soft. Comput. Decis. Anal.

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How to effectively deal with uncertain and imprecise information in decision making is a complex task. Dempster-Shafer evidence theory (DSET) is widely used for handling such challenges due to its ability to model uncertainty and imprecision. However, Dempster's rule can sometimes yield counterintuitive results when dealing with highly conflicting evidence. In this paper, we introduce a novel belief sine similarity measure, called $BS^2M$, which effectively measures the discrepancy between different pieces of evidence. We also establish that $BS^2M$ possesses important properties such as boundedness, symmetry, and non-degeneracy. Building upon $BS^2M$, we present a new method for decision making. The proposed method considers both the credibility and the information volume of each evidence, providing a more comprehensive reflection of their importance. To validate our method, we conduct experiment in target recognition application, demonstrating the effectiveness and rationality of the proposed method.

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Novel Distance Measures of Picture Fuzzy Sets and Their Applications

Zhu,

Liu,

Ur Rahman

2024

Arab J Sci Eng

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A belief Sharma-Mittal divergence with its application in multi-sensor information fusion

Cited by 10 publications

References 42 publications

International Comparison on the Application of Information Technology in High School Mathematics Textbooks

International Comparison on the Application of Information Technology in High School Mathematics Textbooks

A Belief Similarity Measure for Dempster-Shafer Evidence Theory and Application in Decision Making

Novel Distance Measures of Picture Fuzzy Sets and Their Applications

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