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time-series-forecasting-keras

The experimental source code of Paper: Time Series Forecasting using GRU Neural Network with Multi-lag after Decomposition, ICONIP 2017. paper, HomePage

Requirements

  • python 3.6.3 (Anaconda)
  • keras 2.1.2
  • tensorflow-gpu 1.13.1
  • sklearn 0.19.1
  • numpy 1.15.4
  • pandas 0.23.4
  • statsmodels 0.8.0
  • matplotlib 2.1.0

Model

  • LSTM
  • GRU
  • RNN
  • MLP
  • SVR
  • ARIMA
  • time series decomposition

Code

  • data
  • models
    • decompose.py: time series decomposition
    • MLP.py: MLP network
    • RNNS.py: RNN faimily network, including RNN, LSTM, GRU
    • SVR.py: SVR model
  • naive_MLP_forecasting.py
  • naive_RNN_forecasting.py
  • naive_SVR_forecasting.py
  • decompose_MLP_forecasting.py
  • decompose_RNN_forecasting.py
  • decompose_SVR_forecasting.py
  • ARIMA.py (to do)
  • util.py: load data, pre-processe time series, including multi-lag sampling
  • eval.py: calculate the metrics
  • subseries_plot.py: plot figure of time series decomposition

time-series-forecasting-keras's People

Contributors

zhangxu0307 avatar

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