Random Permutation Set


  • Yong Deng University of Electronic Science and Technology of China, Chengdu, China




Dempster-Shafer evidence theory, Permutation number, Random permutation set, Permutation mass function, Orthogonal sum, Random finite set, Threat assessment


For exploring the meaning of the power set in evidence theory, a possible explanation of power set is proposed from the view of Pascal’s triangle and combinatorial number. Here comes the question: what would happen if the combinatorial number is replaced by permutation number? To address this issue, a new kind of set, named as random permutation set (RPS), is proposed in this paper, which consists of permutation event space (PES) and permutation mass function (PMF). The PES of a certain set considers all the permutation of that set. The elements of PES are called the permutation events. PMF describes the chance of a certain permutation event that would happen. Based on PES and PMF, RPS can be viewed as a permutation-based generalization of random finite set. Besides, the right intersection (RI) and left intersection (LI) of permutation events are presented. Based on RI and LI, the right orthogonal sum (ROS) and left orthogonal sum (LOS) of PMFs are proposed. In addition, numerical examples are shown to illustrate the proposed conceptions. The comparisons of probability theory, evidence theory, and RPS are discussed and summarized. Moreover, an RPS-based data fusion algorithm is proposed and applied in threat assessment. The experimental results show that the proposed RPS-based algorithm can reasonably and efficiently deal with uncertainty in threat assessment with respect to threat ranking and reliability ranking.

Author Biography

Yong Deng, University of Electronic Science and Technology of China, Chengdu, China

1. Institute of Fundamental and Frontier Science University of Electronic Science and Technology of China, Chengdu, China 2. School of Education Shaanxi Normal University, Xi’an, China 3. School of Knowledge Science Japan Advanced Institute of Science and Technology,  Japan 4. Department of Management, Technology, and Economics ETH Zurich,  Switzerland



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