A.9: LioNets on Time Series: Difference between revisions
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• '''Asset Type''': Jupyter Notebook | • '''Asset Type''': Jupyter Notebook | ||
• '''AI Breadth''': ML, | • '''AI Breadth''': ML, Neural Networks | ||
• '''Learning Ability''': Interpretable ML, Classification, Regression | • '''Learning Ability''': Interpretable ML, Classification, Regression | ||
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• '''License Information''': GNU General Public License (GPL) v3 | • '''License Information''': GNU General Public License (GPL) v3 | ||
• '''Related to circularity and sustainability''': | • '''Related to circularity and sustainability''': Not directly | ||
• '''Audience''': Manufacturers | • '''Audience''': Manufacturers | ||
Latest revision as of 09:20, 27 December 2024
• Short Description: LioNets technique applied to the Turbofan Engine Degradation Simulation dataset (time-series data) LioNets on Time Series.
• Reference, URL: https://www.ai4europe.eu/research/ai-catalog/lionets-time-series
• Applicable Business Category: Manufacturing
• Application in relevant Projects/Initiatives: N.A.
• Asset Type: Jupyter Notebook
• AI Breadth: ML, Neural Networks
• Learning Ability: Interpretable ML, Classification, Regression
• Related technologies: Python Notebooks
• Applicable Research Area: Explainable AI
• Applicable Technical Category: Machine Learning, Robotics and automation
• License Information: GNU General Public License (GPL) v3
• Related to circularity and sustainability: Not directly
• Audience: Manufacturers
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