A total of 21717 parameters have been included in the LSTM NN designed in this study.

Three LSTM layers of 32 neurons were used with 1 hidden layer of 10 feed-forward neurons and 1 output layer of 1 neuron. Input shape for LSTM layers were determined form the batch size (10), the number of past inputs considered in the time series (70) and the number of neurons of the layer.

本架构采用3层各含32个神经元的长短期记忆（Long Short-Term Memory, LSTM）网络，搭配1层含10个神经元的隐藏前馈层与1层含1个神经元的输出层。LSTM层的输入形状由批量大小（10）、时间序列中所考量的过往输入序列长度（70）以及该层的神经元数量共同确定。