A Battlefield Target Grouping Method Based on M-CFSFDP Algorithm
Target grouping can divide battlefield targets into battle space groups. In this way, the target grouping reduces the difficulty of situation assessment and increases the efficiency of decision. In order to solve the target grouping, a target grouping method based on Manifold-CFSFDP algorithm is pro...
| Format: | Article |
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| Language: | zho |
| Published: |
EDP Sciences
2018-12-01
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| Series: | Xibei Gongye Daxue Xuebao |
| Subjects: | |
| Online Access: | https://www.jnwpu.org/articles/jnwpu/pdf/2018/06/jnwpu2018366p1121.pdf |
| _version_ | 1797668822707077120 |
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| collection | DOAJ |
| description | Target grouping can divide battlefield targets into battle space groups. In this way, the target grouping reduces the difficulty of situation assessment and increases the efficiency of decision. In order to solve the target grouping, a target grouping method based on Manifold-CFSFDP algorithm is proposed. This method turns target grouping into dataset clustering. After calculating the manifold which measures the similarity of targets, it searches the clustering centers and classifies the other data points by CFSFDP based on manifold. The simulation experiment for artificial and UCI datasets proves that M-CFSFDP is more effective than CFSFDP. The correctness and feasibility of M-CFSFDP are also shown by static and dynamic grouping of battlefield targets. |
| first_indexed | 2024-03-11T20:35:04Z |
| format | Article |
| id | doaj.art-2c045e2a0c2144b68014ee468e51632d |
| institution | Directory Open Access Journal |
| issn | 1000-2758 2609-7125 |
| language | zho |
| last_indexed | 2024-03-11T20:35:04Z |
| publishDate | 2018-12-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | Xibei Gongye Daxue Xuebao |
| spelling | doaj.art-2c045e2a0c2144b68014ee468e51632d2023-10-02T07:01:40ZzhoEDP SciencesXibei Gongye Daxue Xuebao1000-27582609-71252018-12-013661121112810.1051/jnwpu/20183661121jnwpu2018366p1121A Battlefield Target Grouping Method Based on M-CFSFDP Algorithm0123School of Automation, Northwestern Polytechnical UniversitySchool of Automation, Northwestern Polytechnical UniversitySchool of Automation, Northwestern Polytechnical UniversityAVIC Xi'an Flight Automatic Control Research InstituteTarget grouping can divide battlefield targets into battle space groups. In this way, the target grouping reduces the difficulty of situation assessment and increases the efficiency of decision. In order to solve the target grouping, a target grouping method based on Manifold-CFSFDP algorithm is proposed. This method turns target grouping into dataset clustering. After calculating the manifold which measures the similarity of targets, it searches the clustering centers and classifies the other data points by CFSFDP based on manifold. The simulation experiment for artificial and UCI datasets proves that M-CFSFDP is more effective than CFSFDP. The correctness and feasibility of M-CFSFDP are also shown by static and dynamic grouping of battlefield targets.https://www.jnwpu.org/articles/jnwpu/pdf/2018/06/jnwpu2018366p1121.pdfsituation assessmenttarget groupingmanifoldcfsfdpdynamic grouping |
| spellingShingle | A Battlefield Target Grouping Method Based on M-CFSFDP Algorithm Xibei Gongye Daxue Xuebao situation assessment target grouping manifold cfsfdp dynamic grouping |
| title | A Battlefield Target Grouping Method Based on M-CFSFDP Algorithm |
| title_full | A Battlefield Target Grouping Method Based on M-CFSFDP Algorithm |
| title_fullStr | A Battlefield Target Grouping Method Based on M-CFSFDP Algorithm |
| title_full_unstemmed | A Battlefield Target Grouping Method Based on M-CFSFDP Algorithm |
| title_short | A Battlefield Target Grouping Method Based on M-CFSFDP Algorithm |
| title_sort | battlefield target grouping method based on m cfsfdp algorithm |
| topic | situation assessment target grouping manifold cfsfdp dynamic grouping |
| url | https://www.jnwpu.org/articles/jnwpu/pdf/2018/06/jnwpu2018366p1121.pdf |