Network traffic forecasting with transfer learning-based algorithm for long continuous missing data

Yang Yang

doi:10.1016/j.eswa.2025.129484

Network traffic forecasting with transfer learning-based algorithm for long continuous missing data

2025-09-04

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DOI：10.1016/j.eswa.2025.129484

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Abstract

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• A new framework forecasts traffic with long missing periods. • Transfer learning imputes long continuous missing data. • Signal decomposition simplifies complex imputed time series. • High accuracy validated on real-world power grid traffic.

Network traffic forecasting with transfer learning-based algorithm for long continuous missing data

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