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/
URL: Workflow Template https://hub.knime.com/-/spaces/-/~acxQcWj9lyHLyyrh/
URL: CWEEDS Data https://climate.weather.gc.ca/prods_servs/engineering_e.html
URL: Multivariate Time Series Analysis: LSTMs & Codeless https://www.knime.com/blog/multivariate-time-series-analysis-lstm-codeless
To use this workflow in KNIME, download it from the below URL and open it in KNIME:
Download WorkflowDeploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.
Try NodePit Runner!