Hub
Pricing About
WorkflowWorkflow

Energy Demand Prediction with LSTM - Deployment

Time SeriesPredictionEnergy UsageLSTMDeep Learning
+2
kathrin profile image
Version1.0Latest, created on 
Mar 11, 2025 12:06 PM
Drag & drop
Like
Download workflow
Workflow preview
This workflow applies an LSTM network to predict energy demand using lagged values of a time series as input.

External resources

  • "Once Upon A Time..." by LSTM Network
Loading deploymentsLoading ad hoc jobs

Used extensions & nodes

Created with KNIME Analytics Platform version 4.2.3
  • Go to item
    KNIME Base nodesTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.2.2

    knime
  • Go to item
    KNIME Deep Learning - Keras IntegrationTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.2.1

    knime
  • Go to item
    KNIME Deep Learning - TensorFlow IntegrationTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.2.0

    knime
  • Go to item
    KNIME JavasnippetTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.2.0

    knime
  • Go to item
    KNIME PlotlyTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.2.0

    knime
  • Go to item
    KNIME Quick FormsTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.2.2

    knime

Legal

By using or downloading the workflow, you agree to our terms and conditions.

KNIME
Open for Innovation

KNIME AG
Talacker 50
8001 Zurich, Switzerland
  • Software
  • Getting started
  • Documentation
  • Courses + Certification
  • Solutions
  • KNIME Hub
  • KNIME Forum
  • Blog
  • Events
  • Partner
  • Developers
  • KNIME Home
  • Careers
  • Contact us
Download KNIME Analytics Platform Read more about KNIME Business Hub
© 2025 KNIME AG. All rights reserved.
  • Trademarks
  • Imprint
  • Privacy
  • Terms & Conditions
  • Data Processing Agreement
  • Credits