MS-TVNet:A Long-Term Time Series Prediction Method Based on Multi-Scale Dynamic Convolution

• URL: http://arxiv.org/abs/2506.17253v2
• Date: Wed, 25 Jun 2025 07:55:20 GMT
• Title: MS-TVNet:A Long-Term Time Series Prediction Method Based on Multi-Scale Dynamic Convolution
• Authors: Chenghan Li, Mingchen Li, Yipu Liao, Ruisheng Diao,
• Abstract summary: We propose MS-TVNet, a multi-scale 3D dynamic convolutional neural network.<n>Our findings highlight the effectiveness of leveraging convolutional networks for capturing complex temporal patterns.
• Score: 6.712251433139411
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Long-term time series prediction has predominantly relied on Transformer and MLP models, while the potential of convolutional networks in this domain remains underexplored. To address this gap, we introduce a novel multi-scale time series reshape module, which effectively captures the relationships among multi-period patches and variable dependencies. Building upon this module, we propose MS-TVNet, a multi-scale 3D dynamic convolutional neural network. Through comprehensive evaluations on diverse datasets, MS-TVNet demonstrates superior performance compared to baseline models, achieving state-of-the-art (SOTA) results in long-term time series prediction. Our findings highlight the effectiveness of leveraging convolutional networks for capturing complex temporal patterns, suggesting a promising direction for future research in this field.The code is realsed on https://github.com/Curyyfaust/TVNet.

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