聚类分析
鉴定(生物学)
人工智能
计算机科学
数学
辨别力
肘部
帧(网络)
植物
医学
电信
生物
认识论
哲学
外科
标识
DOI:10.1109/tfuzz.2020.2966182
摘要
Generalized evidence theory as an extension of Dempster-Shafer evidence theory can deal with uncertain information fusion in the open world. However, one of the open issues is to detect the number of unknown targets. In this article, a new method based on the elbow method is proposed to solve this problem. After the identification of the open world, K-means clustering is used to cluster categories. Then, the elbow method is used to find a correct number of unknown targets. The frame of discernment is reupdated. To test effectiveness of the proposed method, several experiments are conducted. The results illustrate the advantage of the proposed method in the open world.
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