GLOBAL HORIZONTAL IRRADIANCE MULTIVARIANT LSTM FORECAST MODEL - TRAINING
The University of Saskatchewan
Ph.D. in Interdisciplinary Studies
Created by: Carlos Enrique Diaz, MBM, B.Eng.
Email: carlos.diaz@usask.ca
Supervisor: Lori Bradford, Ph.D.
Email: lori.bradford@usask.ca
This is a simple example workflow for multivariant time series analysis using an LSTM based recurrent neural network and implemented via the KNIME Deep Learning - Keras Integration.
This workflow used GHI data from CWEEDS for Saskatoon and trains a model to predict the Global Horizontal Irradiance (GHI) in the next hour based on the values in the last 10 hours. The workflow was adapted from the following workflow:
https://hub.knime.com/-/spaces/-/~acxQcWj9lyHLyyrh/
The University of Saskatchewan
Ph.D. in Interdisciplinary Studies
Created by: Carlos Enrique Diaz, MBM, B.Eng.
Email: carlos.diaz@usask.ca
Supervisor: Lori Bradford, Ph.D.
Email: lori.bradford@usask.ca
This is a simple example workflow for multivariant time series analysis using an LSTM based recurrent neural network and implemented via the KNIME Deep Learning - Keras Integration.
This workflow used GHI data from CWEEDS for Saskatoon and trains a model to predict the Global Horizontal Irradiance (GHI) in the next hour based on the values in the last 10 hours. The workflow was adapted from the following workflow:
https://hub.knime.com/-/spaces/-/~acxQcWj9lyHLyyrh/