1: TRUE Connector MVDS: Difference between revisions

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• '''Short Description''':  
• '''Purpose/Short Description''':  
Functions for training and evaluation of a stacked LSTM model to predict the time to produce a given item


• '''Reference, URL''': https://www.ai4europe.eu/research/ai-catalog/time-prediction-flexible-manufacturing
• '''Applicable Data Spaces Building Block (see DSCC Buildign Blocks)''':Data Sovereignty & Trust


• '''Applicable Business Category''': Manufacturing
• '''Reference, URL''':  


• '''Application in relevant Projects/Initiatives''': AI4EU
• '''Completion Date ''':


• '''Asset Type''': Jupyter Notebook
• '''Challenge addressed''':  


• '''AI Breadth''': ML, LSTM
• '''Applicable Business area ''':


• '''Learning Ability''': Deep learning, LSTM, Time series
• '''Affected Stakeholders''':


• '''Related technologies''': Python
• '''Key components''':  


• '''Applicable Research Area''': Integrative AI
• '''Benefits'':
 
• '''Applicable Technical Category''': Machine Learning
 
• '''License Information''': MIT license (MIT)
 
• '''Related to circularity and sustainability''':  Yes
 
• '''Audience''': Manufacturers


• '''Metrics/KPIs''': Machine Learning






Go back to the '''[[Solutions for circularity Data Space implementations]]'''
Go back to the '''[[Solutions for circularity Data Space implementations]]'''

Revision as of 11:07, 27 December 2024

Purpose/Short Description:

Applicable Data Spaces Building Block (see DSCC Buildign Blocks):Data Sovereignty & Trust

Reference, URL:

Completion Date :

Challenge addressed:

Applicable Business area :

Affected Stakeholders:

Key components:

• 'Benefits:

Metrics/KPIs: Machine Learning


Go back to the Solutions for circularity Data Space implementations