A Data-Driven Method for Power System Transient Instability Mode Identification Based on Knowledge Discovery and XGBoost Algorithm
Aiming at the difficulty of unstable pattern recognition after power system fault, a novel identification framework for transient instability mode identification based on knowledge discovery by accuracy maximization (KODAMA) and extreme gradient boosting (XGBoost) algorithm is proposed. In this meth...
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| Autores principales: | , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
IEEE
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/0d7ed6350b6f4095991d74927eaf5cd8 |
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