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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...
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Published in: | Symmetry (Basel) 2022-10, Vol.14 (10), p.1992 |
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container_issue | 10 |
container_start_page | 1992 |
container_title | Symmetry (Basel) |
container_volume | 14 |
creator | Wang, Senlin Nie, Dangmin |
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. |
doi_str_mv | 10.3390/sym14101992 |
format | article |
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subjects | Accuracy Aircraft accidents & safety Algorithms Aviation Bayesian optimization Classification flight conflict detection Flight safety Game theory Machine learning Methods Normal distribution Probability relevance vector machine Resampling Sparsity Support vector machines Training |
title | Flight Conflict Detection Algorithm Based on Relevance Vector Machine |
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