Permutation Jensen-Shannon divergence for Random Permutation Set

被引:31
作者
Chen, Luyuan [1 ]
Deng, Yong [1 ,2 ,3 ,4 ]
Cheong, Kang Hao [5 ]
机构
[1] Univ Elect Sci & Technol China, Inst Fundamental & Frontier Sci, Chengdu, Peoples R China
[2] Shaanxi Normal Univ, Sch Educ, Xian, Peoples R China
[3] Japan Adv Inst Sci & Technol, Sch Knowledge Sci, Nomi, Ishikawa 9231211, Japan
[4] Swiss Fed Inst Technol, Dept Management Technol & Econ, Zurich, Switzerland
[5] Singapore Univ Technol & Design, Sci Math & Technol Cluster, S-487372 Singapore, Singapore
基金
中国国家自然科学基金;
关键词
Divergence measure; Jensen-Shannon divergence; Random permutation set; Evidence theory; Data fusion; Threat assessment; DIMENSION; FUSION;
D O I
10.1016/j.engappai.2022.105701
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Random Permutation Set (RPS) considers the permutation of elements for a certain set, which is an efficient tool for dealing with uncertainty with ordered information. An important feature of RPS theory is that in the fusion rule of RPS sources, the fusion order has a great impact on fusion results. However, how to determine the fusion order has not yet been discussed. To address this problem, this paper first proposes Permutation Jensen-Shannon (PJS) divergence for measuring the distance between two RPSs. Based on PJS divergence, a new Reliability Assessment algorithm, named RAPJS, is then presented for determining the fusion order of RPSs. The proposed PJS divergence satisfies the properties of non-degeneracy, boundary, and symmetry, and has desirable compatibility with Belief Jensen-Shannon divergence and Jensen-Shannon divergence under certain conditions. The presented RAPJS makes use of the divergence information to calculate the reliability degree of RPS sources, the RPS with a higher reliability is fused first. Experiment results in threat assessment reveal that the presented RAPJS algorithm can determine the fusion order reasonably and effectively. The assessment results using the proposed RAPJS algorithm has the highest target recognition rate compared to other results under different fusion orders.
引用
收藏
页数:9
相关论文
共 74 条
[1]   Reptile Search Algorithm (RSA): A nature-inspired meta-heuristic optimizer [J].
Abualigah, Laith ;
Abd Elaziz, Mohamed ;
Sumari, Putra ;
Geem, Zong Woo ;
Gandomi, Amir H. .
EXPERT SYSTEMS WITH APPLICATIONS, 2022, 191
[2]   Aquila Optimizer: A novel meta-heuristic optimization algorithm [J].
Abualigah, Laith ;
Yousri, Dalia ;
Abd Elaziz, Mohamed ;
Ewees, Ahmed A. ;
Al-qaness, Mohammed A. A. ;
Gandomi, Amir H. .
COMPUTERS & INDUSTRIAL ENGINEERING, 2021, 157 (157)
[3]   The Arithmetic Optimization Algorithm [J].
Abualigah, Laith ;
Diabat, Ali ;
Mirjalili, Seyedali ;
Elaziz, Mohamed Abd ;
Gandomi, Amir H. .
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2021, 376
[4]  
Agushaka J.O., 2022, NEURAL COMPUT APPL, P1
[5]   Dwarf Mongoose Optimization Algorithm [J].
Agushaka, Jeffrey O. ;
Ezugwu, Absalom E. ;
Abualigah, Laith .
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2022, 391
[6]   INTUITIONISTIC FUZZY-SETS [J].
ATANASSOV, KT .
FUZZY SETS AND SYSTEMS, 1986, 20 (01) :87-96
[7]   Eigenvalues of random lifts and polynomials of random permutation matrices [J].
Bordenave, Charles ;
Collins, Benoit .
ANNALS OF MATHEMATICS, 2019, 190 (03) :811-875
[8]   Constrained non-negative sparse coding using learnt instrument templates for realtime music transcription [J].
Carabias-Orti, J. J. ;
Rodriguez-Serrano, F. J. ;
Vera-Candeas, P. ;
Canadas-Quesada, F. J. ;
Ruiz-Reyes, N. .
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2013, 26 (07) :1671-1680
[9]  
Chen L., 2022, COMMUN STAT-THEOR M
[10]   An improved evidential Markov decision making model [J].
Chen, Luyuan ;
Deng, Yong .
APPLIED INTELLIGENCE, 2022, 52 (07) :8008-8017