Similarity evaluation of rocket time series data based on radian features
Evaluating the similarity of rocket time series data is one of the main tasks in rocket time series data analysis. Dynamic time warping (DTW) is the most representative similarity measurement algorithm, but due to its susceptibility to pathological alignment, time points are often mistakenly matched...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
National Computer System Engineering Research Institute of China
2024-02-01
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| Series: | Dianzi Jishu Yingyong |
| Subjects: | |
| Online Access: | http://www.chinaaet.com/article/3000163481 |
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| Summary: | Evaluating the similarity of rocket time series data is one of the main tasks in rocket time series data analysis. Dynamic time warping (DTW) is the most representative similarity measurement algorithm, but due to its susceptibility to pathological alignment, time points are often mistakenly matched, making it difficult to meet the accuracy requirements in the rocket field. To address this issue, this paper proposes a similarity evaluation algorithm for time series data based on radian features. By fully considering the original temporal features and radian features, and using time neighborhood information for calculation, the algorithm's ability to capture the local shape of the sequence has been greatly improved. The proposed algorithm was applied to time series classification task and achieved a classification accuracy improvement of over 26.04% on nine datasets with similar features of rocket data,which proved its effectiveness. |
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| ISSN: | 0258-7998 |