LSTM-MSNet: Leveraging Forecasts on Sets of Related Time Series with Multiple Seasonal Patterns

Generating forecasts for time series with multiple seasonal cycles is an important use-case for many industries nowadays. Accounting for the multi-seasonal patterns becomes necessary to generate more accurate and meaningful forecasts in these contexts... (read more)

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METHOD TYPE
Sigmoid Activation
Activation Functions
Tanh Activation
Activation Functions
Memory Network
Working Memory Models
LSTM
Recurrent Neural Networks