High-Precision prediction of curling trajectory multivariate time series using the novel CasLSTM approach

High-Precision prediction of curling trajectory multivariate time series using the novel CasLSTM approach

Abstract As a multivariate time series, the prediction of curling trajectories is crucial for athletes to devise game strategies. However, the wide prediction range and complex data correlations present significant challenges to this task. This paper puts forward an innovative deep learning approach...

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Bibliographic Details
Main Authors: Yanan Guo, Jing Jin, Hongyang Zhao, Yu Jiang, Dandan Li, Yi Shen
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Curling
Deep learning
Cascade LSTM
Inter-layer memory
Multivariate time series
Multi-step ahead prediction
Online Access:https://doi.org/10.1038/s41598-025-87933-5
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https://doi.org/10.1038/s41598-025-87933-5

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