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Frequency Adaptive Normalization for Time Series by frsgogogo is a document available to read on EtoBox.
What is Frequency Adaptive Normalization for Time Series about?
This paper introduces Frequency Adaptive Normalization (FAN), a novel method for forecasting non-stationary time series that addresses both dynamic trends and seasonal patterns using Fourier transform. FAN improves predictive accuracy by filtering out dominant frequency components and modeling the evolution of these components between inputs and outputs with a simple MLP model. The method demonstrates significant performance improvements across various forecasting models and benchmark datasets, achieving av
- Author
- frsgogogo
- Language
- EN