Support vector machines for transient stability analysis of large-scale power systems

By L. S. Moulin, A.P.A. da Silva, Mohamed A. El-Sharkawi, Robert J. Marks II. IEEE Transactions on Power Systems, 2004

363 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/298432c26645143fe70e1d470dcc9a6d6b591cad

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Carlos Fernandez-Lozano
2. Nereida Rodriguez-Fernandez
3. José Liñares-Blanco
4. Alejandro Pazos
5. Paula Carracedo-Reboredo
6. Victor Maojo
7. Francisco Cedron
8. Adrián Carballal

Citations in the corpus

• A review on machine learning approaches and trends in drug discovery (2021, methodology): “Machine learning techniques, kernel-based methods and SVM more specifically, have proven to be exceptionally efficient in high dimensionality classification problems [132,133] due to their ability to generalize into such spaces, as in the case of texture analysis.”