Sensor Data Fusion Based on a New Conflict Measure
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 sim...
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2016/5769061 |
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doaj-1fc8ef7729b04c3c80d7fbfe20d86e462020-11-24T23:24:45ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472016-01-01201610.1155/2016/57690615769061Sensor Data Fusion Based on a New Conflict MeasureWen Jiang0Boya Wei1Xiyun Qin2Jun Zhan3Yongchuan Tang4School of Electronics and Information, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, ChinaDempster-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.http://dx.doi.org/10.1155/2016/5769061 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Wen Jiang Boya Wei Xiyun Qin Jun Zhan Yongchuan Tang |
spellingShingle |
Wen Jiang Boya Wei Xiyun Qin Jun Zhan Yongchuan Tang Sensor Data Fusion Based on a New Conflict Measure Mathematical Problems in Engineering |
author_facet |
Wen Jiang Boya Wei Xiyun Qin Jun Zhan Yongchuan Tang |
author_sort |
Wen Jiang |
title |
Sensor Data Fusion Based on a New Conflict Measure |
title_short |
Sensor Data Fusion Based on a New Conflict Measure |
title_full |
Sensor Data Fusion Based on a New Conflict Measure |
title_fullStr |
Sensor Data Fusion Based on a New Conflict Measure |
title_full_unstemmed |
Sensor Data Fusion Based on a New Conflict Measure |
title_sort |
sensor data fusion based on a new conflict measure |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2016-01-01 |
description |
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. |
url |
http://dx.doi.org/10.1155/2016/5769061 |
work_keys_str_mv |
AT wenjiang sensordatafusionbasedonanewconflictmeasure AT boyawei sensordatafusionbasedonanewconflictmeasure AT xiyunqin sensordatafusionbasedonanewconflictmeasure AT junzhan sensordatafusionbasedonanewconflictmeasure AT yongchuantang sensordatafusionbasedonanewconflictmeasure |
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1725559000123047936 |