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A modular neural network scheme applied to fault diagnosis in electric power systems

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A modular neural network scheme applied to fault diagnosis in electric power systems

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Flores, A.; Quiles Cucarella, E.; García Moreno, E.; Morant Anglada, FJ.; Correcher Salvador, A. (2014). A modular neural network scheme applied to fault diagnosis in electric power systems. Scientific World Journal. 2014:1-13. doi:10.1155/2014/176463

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/62793

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Title: A modular neural network scheme applied to fault diagnosis in electric power systems
Author: Flores, Agustin Quiles Cucarella, Eduardo García Moreno, Emilio Morant Anglada, Francisco José Correcher Salvador, Antonio
UPV Unit: Universitat Politècnica de València. Departamento de Ingeniería de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica
Issued date:
Abstract:
This work proposes a new method for fault diagnosis in electric power systems based on neural modules. With this method the diagnosis is performed by assigning a neural module for each type of component comprising the ...[+]
Subjects: Mathematics , Computer Science , Medical Laboratory Technology , Physics
Copyrigths: Reconocimiento (by)
Source:
Scientific World Journal. (issn: 1537-744X )
DOI: 10.1155/2014/176463
Publisher:
Hindawi Publishing Corporation
Publisher version: http://dx.doi.org/10.1155/2014/176463
Type: Artículo

References

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Aggarwal, R., & Song, Y. (1997). Artificial neural networks in power systems. Part 1: General introduction to neural computing. Power Engineering Journal, 11(3), 129-134. doi:10.1049/pe:19970306

Faria, L., Silva, A., Vale, Z., & Marques, A. (2009). Training Control Centers’ Operators in Incident Diagnosis and Power Restoration Using Intelligent Tutoring Systems. IEEE Transactions on Learning Technologies, 2(2), 135-147. doi:10.1109/tlt.2009.16 [+]
Yongli, Z., Limin, H., & Jinling, L. (2006). Bayesian Networks-Based Approach for Power Systems Fault Diagnosis. IEEE Transactions on Power Delivery, 21(2), 634-639. doi:10.1109/tpwrd.2005.858774

Aggarwal, R., & Song, Y. (1997). Artificial neural networks in power systems. Part 1: General introduction to neural computing. Power Engineering Journal, 11(3), 129-134. doi:10.1049/pe:19970306

Faria, L., Silva, A., Vale, Z., & Marques, A. (2009). Training Control Centers’ Operators in Incident Diagnosis and Power Restoration Using Intelligent Tutoring Systems. IEEE Transactions on Learning Technologies, 2(2), 135-147. doi:10.1109/tlt.2009.16

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Guo, W., Wen, F., Ledwich, G., Liao, Z., He, X., & Liang, J. (2010). An Analytic Model for Fault Diagnosis in Power Systems Considering Malfunctions of Protective Relays and Circuit Breakers. IEEE Transactions on Power Delivery, 25(3), 1393-1401. doi:10.1109/tpwrd.2010.2048344

Ravikumar, B., Thukaram, D., & Khincha, H. P. (2008). Application of support vector machines for fault diagnosis in power transmission system. IET Generation, Transmission & Distribution, 2(1), 119. doi:10.1049/iet-gtd:20070071

Aggarwal, R., & Yonghua Song. (1998). Artificial neural networks in power systems. Part 2: Types of artificial neural networks. Power Engineering Journal, 12(1), 41-47. doi:10.1049/pe:19980110

Salim, R. H., de Oliveira, K., Filomena, A. D., Resener, M., & Bretas, A. S. (2008). Hybrid Fault Diagnosis Scheme Implementation for Power Distribution Systems Automation. IEEE Transactions on Power Delivery, 23(4), 1846-1856. doi:10.1109/tpwrd.2008.917919

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