Disturbance estimation for floating wind turbine using capsule networks and Actor-Critic federated learning.

<p>Disturbance estimation for floating wind turbine using capsule networks and Actor-Critic federated learning.</p>

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Bibliographic Details
Main Author:	Hadi Mohammadian KhalafAnsar (22783784) (author)
Other Authors:	Jafar Keighobadi (22783787) (author), Mohsen Shahhosseini (11215551) (author)
Published:	2025
Subjects:	Ecology Space Science Biological Sciences not elsewhere classified variable weather conditions unpredictable external inputs research work finds particularly sea waves innovative method based federated deep learning employing federated learning deep reinforcement learning dynamic environmental conditions coarse environmental situation sliding mode control significant oscillatory conditions robust control mechanisms erratic ocean environments control system makes training capsule networks capsule networks framework fwts &# 8217 environmental uncertainty significant advancement ocean wave wide features unique mixture turn improves substantial impact strongly influenced spatial relationships similar systems sensor data proposed technique net model intelligent management high potential fwts among final aim enhanced accuracy disturbance detection critical essential anomaly detection
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