An improved method to determine basic probability assignment with interval number and its application in classification
Due to its efficiency to handle uncertain information, Dempster–Shafer evidence theory has become the most important tool in many information fusion systems. However, how to determine basic probability assignment, which is the first step in evidence theory, is still an open issue. In this article, a...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi - SAGE Publishing
2019-01-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147718820524 |
| _version_ | 1797717447853211648 |
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| author | Bowen Qin Fuyuan Xiao |
| author_facet | Bowen Qin Fuyuan Xiao |
| author_sort | Bowen Qin |
| collection | DOAJ |
| description | Due to its efficiency to handle uncertain information, Dempster–Shafer evidence theory has become the most important tool in many information fusion systems. However, how to determine basic probability assignment, which is the first step in evidence theory, is still an open issue. In this article, a new method integrating interval number theory and k -means++ cluster method is proposed to determine basic probability assignment. At first, k -means++ clustering method is used to calculate lower and upper bound values of interval number with training data. Then, the differentiation degree based on distance and similarity of interval number between the test sample and constructed models are defined to generate basic probability assignment. Finally, Dempster’s combination rule is used to combine multiple basic probability assignments to get the final basic probability assignment. The experiments on Iris data set that is widely used in classification problem illustrated that the proposed method is effective in determining basic probability assignment and classification problem, and the proposed method shows more accurate results in which the classification accuracy reaches 96.7%. |
| first_indexed | 2024-03-12T08:37:25Z |
| format | Article |
| id | doaj.art-1425d59b926847cfb3ff0cecb75e299f |
| institution | Directory Open Access Journal |
| issn | 1550-1477 |
| language | English |
| last_indexed | 2024-03-12T08:37:25Z |
| publishDate | 2019-01-01 |
| publisher | Hindawi - SAGE Publishing |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj.art-1425d59b926847cfb3ff0cecb75e299f2023-09-02T17:09:20ZengHindawi - SAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772019-01-011510.1177/1550147718820524An improved method to determine basic probability assignment with interval number and its application in classificationBowen QinFuyuan XiaoDue to its efficiency to handle uncertain information, Dempster–Shafer evidence theory has become the most important tool in many information fusion systems. However, how to determine basic probability assignment, which is the first step in evidence theory, is still an open issue. In this article, a new method integrating interval number theory and k -means++ cluster method is proposed to determine basic probability assignment. At first, k -means++ clustering method is used to calculate lower and upper bound values of interval number with training data. Then, the differentiation degree based on distance and similarity of interval number between the test sample and constructed models are defined to generate basic probability assignment. Finally, Dempster’s combination rule is used to combine multiple basic probability assignments to get the final basic probability assignment. The experiments on Iris data set that is widely used in classification problem illustrated that the proposed method is effective in determining basic probability assignment and classification problem, and the proposed method shows more accurate results in which the classification accuracy reaches 96.7%.https://doi.org/10.1177/1550147718820524 |
| spellingShingle | Bowen Qin Fuyuan Xiao An improved method to determine basic probability assignment with interval number and its application in classification International Journal of Distributed Sensor Networks |
| title | An improved method to determine basic probability assignment with interval number and its application in classification |
| title_full | An improved method to determine basic probability assignment with interval number and its application in classification |
| title_fullStr | An improved method to determine basic probability assignment with interval number and its application in classification |
| title_full_unstemmed | An improved method to determine basic probability assignment with interval number and its application in classification |
| title_short | An improved method to determine basic probability assignment with interval number and its application in classification |
| title_sort | improved method to determine basic probability assignment with interval number and its application in classification |
| url | https://doi.org/10.1177/1550147718820524 |
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