Comparison on Mean Average Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE) of LSTM and hybrid model.

مواد مشابهة

• Prospective validation of the hybrid model (SEIR-LSTM) and the pure machine learning model (LSTM) on average weekly case case data for all districts in 2019 (A) and per district aggregated mean absolute error (MAE) of the SEIR-LSTM model (B).
  حسب: Yichao Liu (3982652)
  منشور في: (2025)
• Models evaluated during model selection and validation. Model I includes only socioeconomic covariates. Model II to V include socioeconomic factors and meteorological factors which exhibit lag effects, i.e., mean temperature, precipitation, and mean NDVI. Model V compares the full set excluding corrected covariates with introduction of the shifting strain.
  حسب: Yichao Liu (3982652)
  منشور في: (2025)
• The vertical axis shows MAE values for the model configurations described in Table 2, calculated as the average result across all districts. Models I through IV are evaluated as part of the model selection process, while Models V additionally account for the strain shift and the immunity reduction observed in 2017 with the introduction of DENV-2 and are validated on 2019 prospective data.
  حسب: Yichao Liu (3982652)
  منشور في: (2025)
• List of covariates.
  حسب: Yichao Liu (3982652)
  منشور في: (2025)
• The directional impact of covariates on the cases from the selected hybrid model (V).
  حسب: Yichao Liu (3982652)
  منشور في: (2025)