首页|A GMDA clustering algorithm based on evidential reasoning architecture

A GMDA clustering algorithm based on evidential reasoning architecture

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The traditional clustering algorithm is difficult to deal with the identification and division of uncertain objects distributed in the overlapping region,and aimed at solving this problem,the Evidential Clustering based on General Mixture Decomposition Algorithm(GMDA-EC)is pro-posed.First,the belief classification of target cluster is carried out,and the sample category of tar-get distribution overlapping region is extended.Then,on the basis of General Mixture Decomposition Algorithm(GMDA)clustering,the fusion model of evidence credibility and evi-dence relative entropy is constructed to generate the basic probability assignment of the target and achieve the belief division of the target.Finally,the performance of the algorithm is verified by the synthetic dataset and the measured dataset.The experimental results show that the algorithm can reflect the uncertainty of target clustering results more comprehensively than the traditional probabilistic partition clustering algorithm.

Evidential clusteringCredal partitionEvidential reasoningMixed decompositionGaussian mixture model

Haibin WANG、Xin GUAN、Xiao YI、Shuangming LI、Guidong SUN

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Naval Aviation University,Yantai 264001,China

Unit 92941 of PLA,Huludao 125001,China

Institute of Systems Engineering,Beijing 100082,China

Youth Foundation of National Science Foundation of ChinaExcellent Youth Scholar of the National Defense Science and Technology Foundation of ChinaSpecial Fund for Taishan Scholar Project,China

620015032017-JCJQ-ZQ-003ts201712072

2024

10.1016/j.cja.2023.09.015

中国航空学报(英文版)
中国航空学会

中国航空学报(英文版)

CSTPCDEI
影响因子：0.847
ISSN：1000-9361
年,卷(期)：2024.37(1)
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