"Towards an efficient and interpretable Machine Learning approach for ..."

Ismehene Chahbi, Nourhène Ben Rabah, Ines Ben Tekaya (2022)

> Home

Details and statistics

DOI: 10.1109/AICCSA56895.2022.10017816

access: closed

type: Conference or Workshop Paper

metadata version: 2023-01-26

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - conf/aiccsa/ChahbiRT22
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/aiccsa/ChahbiRT22
Ismehene Chahbi, Nourhène Ben Rabah, Ines Ben Tekaya:
Towards an efficient and interpretable Machine Learning approach for Energy Prediction in Industrial Buildings: A case study in the Steel Industry. AICCSA 2022: 1-8

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.