Aircraft Trajectory Prediction Model Based on Improved GRU Structure

Zexuan Chen, Lan Wang
{"title":"Aircraft Trajectory Prediction Model Based on Improved GRU Structure","authors":"Zexuan Chen, Lan Wang","doi":"10.1109/ICCECE58074.2023.10135263","DOIUrl":null,"url":null,"abstract":"In view of the actual need to predict aircraft trajectory, traditional prediction models often have problems such as insufficient precision and slow training efficiency. By analyzing the target trajectory with temporal characteristics, the Elastic-BiGRU trajectory prediction model is proposed, which combines the Smooth filtering method, the Elastic Network fitting method and the GRU structure, the prediction accuracy of aircraft trajectory is further improved. The experimental results show that the Elastic-BiGRU model compared with Bi-LSTM model and Bi-GRU model, its MSE error is relatively reduced by more than 8% and 11%The Elastic-BiGRU also solves the problem of slow training speed of Bi-LSTM model, and saves about 20% of the time.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCECE58074.2023.10135263","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In view of the actual need to predict aircraft trajectory, traditional prediction models often have problems such as insufficient precision and slow training efficiency. By analyzing the target trajectory with temporal characteristics, the Elastic-BiGRU trajectory prediction model is proposed, which combines the Smooth filtering method, the Elastic Network fitting method and the GRU structure, the prediction accuracy of aircraft trajectory is further improved. The experimental results show that the Elastic-BiGRU model compared with Bi-LSTM model and Bi-GRU model, its MSE error is relatively reduced by more than 8% and 11%The Elastic-BiGRU also solves the problem of slow training speed of Bi-LSTM model, and saves about 20% of the time.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于改进GRU结构的飞机轨迹预测模型
针对飞机轨迹预测的实际需要,传统的预测模型往往存在精度不足、训练效率慢等问题。通过分析具有时间特征的目标弹道,提出了结合平滑滤波方法、弹性网络拟合方法和GRU结构的Elastic- bigru弹道预测模型,进一步提高了飞机弹道的预测精度。实验结果表明,与Bi-LSTM模型和Bi-GRU模型相比,Elastic-BiGRU模型的MSE误差相对减小了8%和11%以上,同时也解决了Bi-LSTM模型训练速度慢的问题,节省了约20%的时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Clutter Edge and Target Detection Method Based on Central Moment Feature Adaptive short-time Fourier transform based on reinforcement learning Design and implementation of carrier aggregation and secure communication in distribution field network Power data attribution revocation searchable encrypted cloud storage Research of Intrusion Detection Based on Neural Network Optimized by Sparrow Search Algorithm
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1