Sensor data fusion based on a new conflict measure
type: Item
instance of: scholarly article
title: Sensor data fusion based on a new conflict measure
zbMATH Open document ID: 1400.68218
DOI: 10.1155/2016/5769061
author: Wen Jiang
author: Boya Wei
author: Xiyun Qin
author: Jun Zhan
author: Yongchuan Tang
published in: Mathematical Problems in Engineering
publication date: 2018-10-12T00:00:00Z
review text: Summary: Dempster-Shafer (D-S) evidence theory has been widely used in various fields. However, how to measure the degree of conflict (similarity) between the bodies of evidence is an open issue. In this paper, in order to solve this problem, firstly we propose a modified cosine similarity to measure the similarity between vectors. Then a new similarity measure of basic probability assignment (BPAs) is proposed based on the modified cosine similarity. The new similarity measure can achieve the reasonable measure of the similarity of BPAs and then efficiently measure the degree of conflict among bodies of evidence. Numerical examples are used to illustrate the effectiveness of the proposed method. Finally, a weighted average method based on the new BPAs similarity is proposed, and an example is used to show the validity of the proposed method.
Mathematics Subject Classification ID: 68T37
zbMATH DE Number: 6953360
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2016/5769061
OpenAlex ID: W2518415416
Wikidata QID: Q59131697
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description: scientific article; zbMATH DE number 6953360