首页|A deep multimodal fusion and multitasking trajectory prediction model for typhoon trajectory prediction to reduce flight scheduling cancellation
A deep multimodal fusion and multitasking trajectory prediction model for typhoon trajectory prediction to reduce flight scheduling cancellation
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NETL
NSTL
万方数据
Natural events have had a significant impact on over-all flight activity,and the aviation industry plays a vital role in helping society cope with the impact of these events.As one of the most impactful weather typhoon seasons appears and con-tinues,airlines operating in threatened areas and passengers having travel plans during this time period will pay close atten-tion to the development of tropical storms.This paper proposes a deep multimodal fusion and multitasking trajectory prediction model that can improve the reliability of typhoon trajectory pre-diction and reduce the quantity of flight scheduling cancellation.The deep multimodal fusion module is formed by deep fusion of the feature output by multiple submodal fusion modules,and the multitask generation module uses longitude and latitude as two related tasks for simultaneous prediction.With more depend-able data accuracy,problems can be analysed rapidly and more efficiently,enabling better decision-making with a proactive ver-sus reactive posture.When multiple modalities coexist,features can be extracted from them simultaneously to supplement each other's information.An actual case study,the typhoon Lichma that swept China in 2019,has demonstrated that the algorithm can effectively reduce the number of unnecessary flight cancel-lations compared to existing flight scheduling and assist the new generation of flight scheduling systems under extreme weather.
NETL
NSTL
万方数据
