A Method to Determine Generalized Basic Probability Assignment in the Open World
Dempster-Shafer evidence theory (D-S theory) has been widely used in many information fusion systems since it was proposed by Dempster and extended by Shafer. However, how to determine the basic probability assignment (BPA), which is the main and first step in D-S theory, is still an open issue, esp...
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doaj-1be1deb8b41e44679d2ace6a944a50842020-11-24T23:50:04ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472016-01-01201610.1155/2016/38786343878634A Method to Determine Generalized Basic Probability Assignment in the Open WorldWen Jiang0Jun Zhan1Deyun Zhou2Xin Li3School 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 evidence theory (D-S theory) has been widely used in many information fusion systems since it was proposed by Dempster and extended by Shafer. However, how to determine the basic probability assignment (BPA), which is the main and first step in D-S theory, is still an open issue, especially when the given environment is in an open world, which means the frame of discernment is incomplete. In this paper, a method to determine generalized basic probability assignment in an open world is proposed. Frame of discernment in an open world is established first, and then the triangular fuzzy number models to identify target in the proposed frame of discernment are established. Pessimistic strategy based on the differentiation degree between model and sample is defined to yield the BPAs for known targets. If the sum of all the BPAs of known targets is over one, then they will be normalized and the BPA of unknown target is assigned to 0; otherwise the BPA of unknown target is equal to 1 minus the sum of all the known targets BPAs. IRIS classification examples illustrated the effectiveness of the proposed method.http://dx.doi.org/10.1155/2016/3878634 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Wen Jiang Jun Zhan Deyun Zhou Xin Li |
spellingShingle |
Wen Jiang Jun Zhan Deyun Zhou Xin Li A Method to Determine Generalized Basic Probability Assignment in the Open World Mathematical Problems in Engineering |
author_facet |
Wen Jiang Jun Zhan Deyun Zhou Xin Li |
author_sort |
Wen Jiang |
title |
A Method to Determine Generalized Basic Probability Assignment in the Open World |
title_short |
A Method to Determine Generalized Basic Probability Assignment in the Open World |
title_full |
A Method to Determine Generalized Basic Probability Assignment in the Open World |
title_fullStr |
A Method to Determine Generalized Basic Probability Assignment in the Open World |
title_full_unstemmed |
A Method to Determine Generalized Basic Probability Assignment in the Open World |
title_sort |
method to determine generalized basic probability assignment in the open world |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2016-01-01 |
description |
Dempster-Shafer evidence theory (D-S theory) has been widely used in many information fusion systems since it was proposed by Dempster and extended by Shafer. However, how to determine the basic probability assignment (BPA), which is the main and first step in D-S theory, is still an open issue, especially when the given environment is in an open world, which means the frame of discernment is incomplete. In this paper, a method to determine generalized basic probability assignment in an open world is proposed. Frame of discernment in an open world is established first, and then the triangular fuzzy number models to identify target in the proposed frame of discernment are established. Pessimistic strategy based on the differentiation degree between model and sample is defined to yield the BPAs for known targets. If the sum of all the BPAs of known targets is over one, then they will be normalized and the BPA of unknown target is assigned to 0; otherwise the BPA of unknown target is equal to 1 minus the sum of all the known targets BPAs. IRIS classification examples illustrated the effectiveness of the proposed method. |
url |
http://dx.doi.org/10.1155/2016/3878634 |
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