A Comparative Assessment of Dimensionality Reduction Techniques for Diagnosing Faults in Smart Grids.
Hossein HassaniRoozbeh Razavi-FarMehrdad SaifPublished in: SMC (2020)
Keyphrases
- dimensionality reduction
- model based diagnosis
- high dimensional data
- fault diagnosis
- principal component analysis
- feature extraction
- fault detection
- high dimensionality
- high dimensional
- data representation
- feature selection
- pattern recognition and machine learning
- dimensionality reduction methods
- lower dimensional
- input space
- low dimensional
- linear discriminant analysis
- principal components
- feature space
- manifold learning
- pattern recognition
- structure preserving
- linear dimensionality reduction
- linear projection
- nonlinear dimensionality reduction
- preprocessing step
- random projections
- singular value decomposition
- data points
- dimension reduction
- fault model
- kernel pca
- genetic algorithm
- error detection
- dynamic systems
- repair actions
- fault detection and diagnosis
- multiple faults
- semi supervised dimensionality reduction
- fault detection and isolation
- test cases
- intrinsic dimensionality
- root cause
- principal components analysis