DimAug-TimesFM: Dimension Augmentation for Long-Term Cloud Demand Forecasting in Few-Shot Scenarios

DimAug-TimesFM: Dimension Augmentation for Long-Term Cloud Demand Forecasting in Few-Shot Scenarios

Accurate long-term cloud demand forecasting is critical for optimizing resource procurement and cost management in cloud computing, yet it remains challenging due to dynamic demand trends, limited historical data, and the poor generalization of existing models in few-shot scenarios. This paper propo...

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Bibliographic Details
Main Authors: Xiaoyi Yang, Qiming Zheng, Xiaoyu Zhu, Mianzhang Luo, Zheng Hou, Jiatai Zhang, Yuqing Lan
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Applied Sciences
Subjects:
time series prediction
data augmentation
finops
cloud demand forecasting
large time series models
Online Access:https://www.mdpi.com/2076-3417/15/7/3450
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