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A clustering based method to complete frame of discernment

2022; Elsevier BV; Volume: 36; Issue: 4 Linguagem: Inglês

10.1016/j.cja.2022.09.022

2588-9230

Wenran YANG, Xinde Li, Yong Deng,

Anomaly Detection Techniques and Applications

When the existing information does not contain all categories, the Generalized Evidence Theory (GET) can deal with information fusion. However, the question of how to determine the number of categories through GET is still intriguing. To address this question, a modified k-means clustering, named centers initialized clustering is proposed, filling the gap of identification and complement of the frame of discernment. Based on this clustering method, the number of categories is determined. The initialized centers selected by center density keep the cluster results constant, enhancing the stability of clustering results. Besides, constructing Generalized basic Probability Assignment (GBPA) modules in a conservative way improves the reliability of the results. The mass of empty set in combined GBPAs is the indicator of the number of categories. Experiments on real and artificial data sets are conducted to show the effectiveness.