"Wind Turbine Hybrid Physics-Based Deep Learning Model for a Health ..."

Nezmin Kayedpour et al. (2024)

> Home

Details and statistics

DOI: 10.1109/TIM.2024.3375416

access: closed

type: Journal Article

metadata version: 2024-04-15

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - journals/tim/KayedpourQWKCC24
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/tim/KayedpourQWKCC24
Nezmin Kayedpour, Jixiang Qing, Jolan Wauters, Jeroen D. M. De Kooning, Ivo Couckuyt, Guillaume Crevecoeur:
Wind Turbine Hybrid Physics-Based Deep Learning Model for a Health Monitoring Approach Considering Provision of Ancillary Services. IEEE Trans. Instrum. Meas. 73: 1-14 (2024)

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.