Título:
Training guidelines for neural networks to estimate stability regions
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Director:
Compilador:
Autor:
Ferreira, Enrique
Krogh, Bruce
Krogh, Bruce
Tutor:
Tipo de documento:
Preprint
Editor:
Palabras clave:
Neural networks
Power system stability
State estimation
Linear systems
Chemical reactors
Nonlinear systems
Power system stability
State estimation
Linear systems
Chemical reactors
Nonlinear systems
Descriptores:
Año de publicación:
1999
Contenido:
Resumen:
This paper presents new results on the use of neural networks to estimate stability regions for autonomous nonlinear systems. In contrast to model-based analytical methods, this approach uses empirical data from the system to train the neural network. A method is developed to generate confidence intervals for the regions identified by the trained neural network. The neural network results are compared with estimates obtained by previously proposed methods for a standard two-dimensional example.
Descripción:
Trabajo presentado a American Control Conference 1999.
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Editorial:
IEEE
EN:
Financiadores:
Citación:
Ferreira, Enrique, Krogh, Bruce. Training guidelines for neural networks to estimate stability regions [Preprint] Publicado en American Control Conference, San Diego, California, 1999.
Citación:
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Licencia:
Licencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC - By-NC-ND)
Colecciones:
| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| FK99.pdf | — | 120.42 KB | Adobe PDF |