Spatio-temporal Stacked LSTM for Temperature Prediction in Weather Forecasting

Understand

Long Short-Term Memory (LSTM) is a well-known method used widely on sequence learning and time series prediction.

• In this paper we deployed stacked LSTM model in an application of weather forecasting.
• We propose a 2-layer spatio-temporal stacked LSTM model which consists of independent LSTM models per location in the first LSTM layer.
• Subsequently, the input of the second LSTM layer is formed based on the combination of the hidden states of the first layer LSTM models.