Limit of the maximum random permutation set entropy

IF 3.1 3区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY Physica A: Statistical Mechanics and its Applications Pub Date : 2025-04-15 Epub Date: 2025-02-10 DOI:10.1016/j.physa.2025.130425
Jiefeng Zhou , Zhen Li , Kang Hao Cheong , Yong Deng
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Abstract

The Random Permutation Set (RPS) is a recently proposed new type of set, which can be regarded as the generalization of evidence theory. To measure the uncertainty of RPS, the entropy of RPS and its corresponding maximum entropy have been proposed. Exploring the maximum entropy provides a possible way to understand the physical meaning of RPS. In this paper, a new concept, the envelope of entropy function, is defined. In addition, the limit of the envelope of RPS entropy is derived and proven. Compared with the existing method, the computational complexity of the proposed method to calculate the envelope of RPS entropy decreases greatly. The result shows that when the cardinality of a RPS (marked as N) approaches to infinity, the limit form of the envelope of the entropy of RPS converges to e(N!)2, which is highly connected to the constant e and factorial. Finally, numerical examples validate the efficiency and conciseness of the proposed envelope, which provides new insights into the maximum entropy function.
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最大随机排列组合熵的极限
随机排列集(RPS)是近年来提出的一种新的集合类型,可以看作是证据理论的推广。为了测量RPS的不确定度,提出了RPS的熵及其对应的最大熵。探索最大熵为理解RPS的物理含义提供了一种可能的方法。本文提出了一个新的概念——熵函数包络。此外,还推导并证明了RPS熵包络的极限。与现有方法相比,该方法计算RPS熵包络的计算复杂度大大降低。结果表明,当RPS(标记为N)的基数趋近于无穷时,RPS的熵包络的极限形式收敛于e⋅(N!)2,它与常数e和阶乘高度相关。最后,数值算例验证了所提包络的有效性和简洁性,为最大熵函数提供了新的见解。
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来源期刊
CiteScore
7.20
自引率
9.10%
发文量
852
审稿时长
6.6 months
期刊介绍: Physica A: Statistical Mechanics and its Applications Recognized by the European Physical Society Physica A publishes research in the field of statistical mechanics and its applications. Statistical mechanics sets out to explain the behaviour of macroscopic systems by studying the statistical properties of their microscopic constituents. Applications of the techniques of statistical mechanics are widespread, and include: applications to physical systems such as solids, liquids and gases; applications to chemical and biological systems (colloids, interfaces, complex fluids, polymers and biopolymers, cell physics); and other interdisciplinary applications to for instance biological, economical and sociological systems.
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