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Finally, the attention mechanism is used to obtain more useful information to improve the recognition accuracy. Through offline recognition experiment, it is proved that A-TSO-PBiGRU can effectively improve the convergence speed and recognition accuracy compared with GRU-related networks. Compared with the other six comparison algorithms, maneuver intention recognition accuracy also has significant advantages. In the online recognition experiment, maneuver intention recognition accuracy of A-TSO-PBiGRU is 93.7%, it shows excellent maneuver intention recognition ability.<\/jats:p>","DOI":"10.1007\/s40747-023-01257-3","type":"journal-article","created":{"date-parts":[[2023,10,30]],"date-time":"2023-10-30T03:01:32Z","timestamp":1698634892000},"page":"2151-2172","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Beyond visual range maneuver intention recognition based on attention enhanced tuna swarm optimization parallel BiGRU"],"prefix":"10.1007","volume":"10","author":[{"given":"Xie","family":"Lei","sequence":"first","affiliation":[]},{"given":"Deng","family":"Shilin","sequence":"additional","affiliation":[]},{"given":"Tang","family":"Shangqin","sequence":"additional","affiliation":[]},{"given":"Huang","family":"Changqiang","sequence":"additional","affiliation":[]},{"given":"Dong","family":"Kangsheng","sequence":"additional","affiliation":[]},{"given":"Zhang","family":"Zhuoran","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,10,30]]},"reference":[{"key":"1257_CR1","doi-asserted-by":"publisher","first-page":"1006","DOI":"10.1016\/j.dt.2021.04.009","volume":"18","author":"WH Li","year":"2022","unstructured":"Li WH, Shi JP, Wu YY et al (2022) A multi-UCAV cooperative occupation method based on weapon engagement zones for beyond-visual-range air combat. 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