A hierarchical power system transient stability assessment method considering sample imbalance
In order to make full use of the dynamic information contained in the electrical quantity response trajectories, improve the reliability of critical sample prediction results, and correct the bias problem caused by sample imbalance to model prediction, a transient stability assessment (TSA) method b...
Guardado en:
Autores principales: | Yixing Du, Zhijian Hu, Fangzhou Wang |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Elsevier
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/63259d483d404d459121ae4f1651c634 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Automated Individual Cattle Identification Using Video Data: A Unified Deep Learning Architecture Approach
por: Yongliang Qiao, et al.
Publicado: (2021) -
Hierarchical Spatiotemporal Electroencephalogram Feature Learning and Emotion Recognition With Attention-Based Antagonism Neural Network
por: Pengwei Zhang, et al.
Publicado: (2021) -
Air Pollutant Concentration Prediction Based on a CEEMDAN-FE-BiLSTM Model
por: Xuchu Jiang, et al.
Publicado: (2021) -
A Novel Data Augmentation Technique and Deep Learning Model for Web Application Security
por: Hacer Karacan, et al.
Publicado: (2021) -
A Bidirectional Long Short-Term Memory Model Algorithm for Predicting COVID-19 in Gulf Countries
por: Theyazn H. H. Aldhyani, et al.
Publicado: (2021)