Machine learningTime-series forecasting
DLinear：时间序列预测的分解线性模型
DLinear是由Zeng等人于2023年在AAAI上提出的一种轻量级时间序列预测模型。它挑战了Transformer架构对于准确的长期预测是必需的普遍假设。该模型使用移动平均滤波器将输入序列分解为趋势和季节性分量，然后对每个分量应用单独的单层线性变换，最后将它们的输出相加得到最终预测。
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来源
- Zeng, A., Chen, M., Zhang, L., & Xu, Q. (2023). Are transformers effective for time series forecasting? AAAI. link ↗
如何引用本页
ScholarGate. (2026, June 2). DLinear (Decomposition Linear Model for Forecasting). ScholarGate. https://scholargate.app/zh/deep-learning/dlinear
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