Flight Conflict Detection Algorithm Based on Relevance Vector Machine
In response to the problems of slow running speed and high error rates of traditional flight conflict detection algorithms, in this paper, we propose a conflict detection algorithm based on the use of a relevance vector machine. A set of symmetrical historical flight data was used as the training se...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-09-01
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| Series: | Symmetry |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-8994/14/10/1992 |
| _version_ | 1797469848433852416 |
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| author | Senlin Wang Dangmin Nie |
| author_facet | Senlin Wang Dangmin Nie |
| author_sort | Senlin Wang |
| collection | DOAJ |
| description | In response to the problems of slow running speed and high error rates of traditional flight conflict detection algorithms, in this paper, we propose a conflict detection algorithm based on the use of a relevance vector machine. A set of symmetrical historical flight data was used as the training set of the model, and we used the SMOTE resampling method to optimize the training set. We obtained relatively symmetrical training data and trained it with the relevance vector machine, improving the kernels through an intelligent algorithm. We tested this method with new symmetrical flight data. The improved algorithm greatly improved the running speed and was able to effectively reduce the missed alarm rate of in-flight conflict detection symmetrically, thus effectively ensuring flight safety. |
| first_indexed | 2024-03-09T19:26:51Z |
| format | Article |
| id | doaj.art-757f609a7e9b46eeb0ae6851cfc1a0fb |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-03-09T19:26:51Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-757f609a7e9b46eeb0ae6851cfc1a0fb2023-11-24T02:50:16ZengMDPI AGSymmetry2073-89942022-09-011410199210.3390/sym14101992Flight Conflict Detection Algorithm Based on Relevance Vector MachineSenlin Wang0Dangmin Nie1Air Traffic Control and Navigation School, Air Force Engineering University, Xi’an 710051, ChinaAir Traffic Control and Navigation School, Air Force Engineering University, Xi’an 710051, ChinaIn response to the problems of slow running speed and high error rates of traditional flight conflict detection algorithms, in this paper, we propose a conflict detection algorithm based on the use of a relevance vector machine. A set of symmetrical historical flight data was used as the training set of the model, and we used the SMOTE resampling method to optimize the training set. We obtained relatively symmetrical training data and trained it with the relevance vector machine, improving the kernels through an intelligent algorithm. We tested this method with new symmetrical flight data. The improved algorithm greatly improved the running speed and was able to effectively reduce the missed alarm rate of in-flight conflict detection symmetrically, thus effectively ensuring flight safety.https://www.mdpi.com/2073-8994/14/10/1992flight conflict detectionrelevance vector machineBayesian optimization |
| spellingShingle | Senlin Wang Dangmin Nie Flight Conflict Detection Algorithm Based on Relevance Vector Machine Symmetry flight conflict detection relevance vector machine Bayesian optimization |
| title | Flight Conflict Detection Algorithm Based on Relevance Vector Machine |
| title_full | Flight Conflict Detection Algorithm Based on Relevance Vector Machine |
| title_fullStr | Flight Conflict Detection Algorithm Based on Relevance Vector Machine |
| title_full_unstemmed | Flight Conflict Detection Algorithm Based on Relevance Vector Machine |
| title_short | Flight Conflict Detection Algorithm Based on Relevance Vector Machine |
| title_sort | flight conflict detection algorithm based on relevance vector machine |
| topic | flight conflict detection relevance vector machine Bayesian optimization |
| url | https://www.mdpi.com/2073-8994/14/10/1992 |
| work_keys_str_mv | AT senlinwang flightconflictdetectionalgorithmbasedonrelevancevectormachine AT dangminnie flightconflictdetectionalgorithmbasedonrelevancevectormachine |