2_ARIMA_Models
ARIMA Models This workflow demonstrates how to predict time series (energy consumption) with an autoregressive integrated moving average (ARIMA) model. […]
03_SARIMA_Models
This workflow predicts the residual of time series (energy consumption) by seasonal autoregressive integrated moving average (ARIMA) models that aim at […]
04_Machine_Learning
This workflow predicts the residual of time series (energy consumption) by machine learning models that use lagged values as predictors. The residual of […]
02_LSTM_Network
This workflow predicts time series (energy consumption) by an LSTM network with lagged values as input. The trained model is then used for out-of-sample […]
Energy Demand Prediction
URL: KNIME Deep Learning Integration Installation Guide https://docs.knime.com/latest/deep_learning_installation_guide/index.html#_introduction
04_Machine_Learning
This workflow predicts the residual of time series (energy consumption) by machine learning models that use lagged values as predictors. The residual of […]
01_Additional_Visualizations
Additional plots to visually explore time series data
02_LSTM_Network1
This workflow predicts time series (energy consumption) by an LSTM network with lagged values as input. The trained model is then used for out-of-sample […]
Daily Weather Time Series Forecasting
Daily Weather Time Series Forecasting This workflow uses the original workflow linked below in order to do a weather forecast (dataset also linked […]
01_Additional_Visualizations
Additional plots to visually explore time series data