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Keyword: short-term wind forecasting ×Clear all

2 claims from 1 paper

1. Earth and Planetary Sciences › Meteorological Phenomena and Simulations

   Short-Term Ground Gust Prediction Based on Fusion of Ground and High-Altitude Meteorological Data and Differential Polynomial Modeling

   Chu, Yan, Zhu et al. · Atmosphere · 2026

   The study proposes TADPN, a lightweight, interpretable neural network for hourly gust forecasting at one Nanjing grid point, reporting lower errors than nine baseline models.

   Unchecked2 claims
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   1. UncheckedIn strictly chronological three-fold rolling validation, the TADPN gust model averaged an error of 0.4197 m/s MAE, 0.6079 m/s RMSE and an R2 of 0.9373.“Strictly chronological three-fold rolling validation yields mean MAE, RMSE, and R2 values of 0.4197 m s−1, 0.6079 m s−1, and 0.9373.”
   2. UncheckedIn this study, the TADPN gust-forecasting model had a mean absolute error 11.88–29.88% lower than nine baseline models.“TADPN reduces MAE by 11.88–29.88% relative to nine baselines.”