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A meta-learning-based short-term holiday system load forecasting method
DOI:10.1016/j.egyr.2026.109517.png)
摘要
En 中文
• 因子解耦模型分离了节日负荷趋势、结构和天气。
• 知识通过三阶段元学习解决数据稀缺问题。
• 元学习通过少量跨节日任务应用于节日预测。
Keyword:
Holiday load forecasting
Meta-learning
Few-shot learning
Factor decoupling
期刊
E
IF:
5.1
论文数:
904
被引数:
0
机构
引用论文
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Electronics
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IEEE ACCESS
IF3.6

