Paper
10 August 2023 Simulation of multi-factor water-floating garbage drift trajectories based on Sa-LSTM
Long Ma, Baijing Wu, Jing Lian, Jianwei Deng
Author Affiliations +
Proceedings Volume 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023); 127591K (2023) https://doi.org/10.1117/12.2686449
Event: 2023 3rd International Conference on Automation Control, Algorithm and Intelligent Bionics (ACAIB 2023), 2023, Xiamen, China
Abstract
To address the issue of low accuracy in simulating the motion trajectory of water-floating garbage due to multiple factors, a method for simulating the drift trajectory of water-floating garbage based on Sa-LSTM was proposed. The method taking the drift trajectory of water-floating garbage in Lanzhou Section of the Yellow River as the research object, integrated multiple influencing factors through feature derivation and enhanced the memory and generalization ability of LSTM model by using spatial attention module, which further improved the accuracy of water-floating garbage simulation data. The experimental results show that the proposed method can effectively reduce the interference of multiple influencing factors on the simulation of water-floating garbage drifting trajectory, improve the accuracy of drifting trajectory simulation, and provide a method and location information support for the accurate management and management of water-floating garbage.
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Long Ma, Baijing Wu, Jing Lian, and Jianwei Deng "Simulation of multi-factor water-floating garbage drift trajectories based on Sa-LSTM", Proc. SPIE 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023), 127591K (10 August 2023); https://doi.org/10.1117/12.2686449
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KEYWORDS
Data modeling

Computer simulations

Neurons

Education and training

Data fusion

Data acquisition

Wind speed

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