@inproceedings{0504ed7fe7a1408fa3a3749f81e8f822,
title = "An LSTM-based Fleet Formation Recognition Algorithm",
abstract = "In this paper, a fleet formation recognition problem is investigated in which a team of ships cooperate to carry out a mission. First, the ship motion model is established and the corresponding fleet formation dataset is generated. Then, a formation recognition algorithm based on Long Short-Term Memory(LSTM) network is proposed. Finally, simulation experimental results show the effectiveness of the proposed algorithm.",
keywords = "Fleet Formation, Formation Recognition, LSTM",
author = "Zhaochen Lin and Xinran Zhang and Ning Hao and Fenghua He",
note = "Publisher Copyright: {\textcopyright} 2021 Technical Committee on Control Theory, Chinese Association of Automation.; 40th Chinese Control Conference, CCC 2021 ; Conference date: 26-07-2021 Through 28-07-2021",
year = "2021",
month = jul,
day = "26",
doi = "10.23919/CCC52363.2021.9550097",
language = "英语",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "8565--8569",
editor = "Chen Peng and Jian Sun",
booktitle = "Proceedings of the 40th Chinese Control Conference, CCC 2021",
address = "美国",
}