A three-stage method combining physical rules, RANSAC regression with IQR thresholds, and mathematical morphology identifies scattered and densely clustered outliers in wind speed-power data better than several baselines.
Time series data-driven online prognosis of wind turbine faults in presence of scada data loss,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.SP 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Three-Stage Composite Outlier Identification of Wind Power Data: Integrating Physical Rules with Regression Learning and Mathematical Morphology
A three-stage method combining physical rules, RANSAC regression with IQR thresholds, and mathematical morphology identifies scattered and densely clustered outliers in wind speed-power data better than several baselines.