Previsões
ID
Idioma
Nome do modelo
Repositório
Descrição
LSTM model for Infodengue Sprint
Predictions for 2024 in SP using the baseline architecture
LSTM model for Infodengue Sprint
Predictions for 2023 in MG using the baseline architecture
LSTM model for Infodengue Sprint
Predictions for 2023 in RJ using the baseline architecture
Temp-SPI Interaction Model
Validation test 1 for three-way interaction model (SC)
Model 2 - Weekly and yearly (rw1) components
The model is founded on a structural decomposition designed for modeling counting series, employing a Poisson distribution. The log intensity is defined by the sum of weekly and yearly components, where the first one is defined as a AR(1) process and the last one is assumed to be iid.
LSTM model for Infodengue Sprint
Predictions for 2023 in RN using the baseline architecture
LSTM model for Infodengue Sprint
Predictions for 2023 in PA using the comb_att_n architecture
Random Forest model with uncertainty computed with conformal prediction
Forecast de novos casos para o geocode 2304400 entre 2022-01-01 e 2023-01-01 usando apenas os dados de 2304400 como input
LSTM model for Infodengue Sprint
Predictions for 2023 in SE using the baseline architecture
Random Forest model with uncertainty computed with conformal prediction
Forecast de novos casos para o geocode 2111300 entre 2022-01-01 e 2023-01-01 usando apenas os dados de todos as cidades clusterizadas com 2111300 como input
Temp-SPI Interaction Model
Validation test 1 for three-way interaction model (GO)
LSTM model for Infodengue Sprint
Predictions for 2023 in RO using the comb_att_n architecture
LSTM model for Infodengue Sprint
Predictions for 2023 in SP using the baseline architecture
Temp-SPI Interaction Model
Validation test 2 for three-way interaction model (AM)
Random Forest model with uncertainty computed with conformal prediction
Forecast de novos casos para o geocode 2704302 entre 2022-01-01 e 2023-01-01 usando apenas os dados de 2704302 como input
Deep learning model using BI-LSTM Layers
Forecast de novos casos para o geocode 2408102 entre 2022-01-01 e 2023-01-01 usando apenas os dados do geocode 2408102
Deep learning model using BI-LSTM Layers
Forecast de novos casos para o geocode 2211001 entre 2022-01-01 e 2023-01-01 usando apenas os dados do geocode e das cidades clusterizadas com ele
700 previsões
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