Previsões
ID
Idioma
Nome do modelo
Repositório
Descrição
LSTM model for Infodengue Sprint
Predictions for 2024 in ES using the baseline architecture
LSTM model for Infodengue Sprint
Predictions for 2023 in MS using the att_3 architecture
LSTM model for Infodengue Sprint
Predictions for 2023 in AP using the comb_att_n architecture
Temp-SPI Interaction Model
Validation test 1 for three-way interaction model (BA)
Model 2 - Weekly and yearly (rw1) components
This upload represents the epidemic prediction for validation test 2 in the state MT.
Model 2 - Weekly and yearly (rw1) components
This upload represents the epidemic prediction for validation test 2 in the state DF.
Model 2 - Weekly and yearly (rw1) components
This upload represents the epidemic prediction for validation test 2 in the state SC.
Model 2 - Weekly and yearly (rw1) components
This upload represents the epidemic prediction for validation test 2 in the state RS.
Model 2 - Weekly and yearly (rw1) components
This upload represents the epidemic prediction for validation test 2 in the state SP.
Model 2 - Weekly and yearly (rw1) components
This upload represents the epidemic prediction for validation test 2 in the state MG.
LSTM model for Infodengue Sprint
Predictions for 2023 in BA using the baseline architecture
Model 1 - Weekly and yearly (iid) 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 PI using the baseline architecture
Model 2 - Weekly and yearly (rw1) components
This upload represents the epidemic prediction for validation test 1 in the state RN.
Model 1 - Weekly and yearly (iid) components
This upload represents the epidemic prediction for validation test 1 in the state AL.
Temp-SPI Interaction Model
Validation test 1 for three-way interaction model (PE)
Temp-SPI Interaction Model
Validation test 2 for three-way interaction model (PE)
Temp-SPI Interaction Model
Validation test 2 for three-way interaction model (RJ)
Temp-SPI Interaction Model
Validation test 2 for three-way interaction model (PB)
LSTM model for Infodengue Sprint
Predictions for 2024 in CE using the baseline_msle architecture
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.
700 previsões
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