Wijayakulasooriya, Janaka V., Putrus, Ghanim and Minns, Peter (2002) Electric power quality disturbance classification using self-adapting artificial neural networks. IEE Proceedings: Generation, Transmission and Distribution, 149 (1). p. 98. ISSN 1350-2360
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Electric power quality disturbance classification using self-adapting artificial neural networks.pdf - Accepted Version Download (107kB) | Preview |
Official URL: http://dx.doi.org/10.1049/ip-gtd:20020014
| Item Type: | Article |
|---|---|
| Additional Information: | This work on the “Power Quality” which is now recognised an essential feature that largely affects the performance of modern power networks. This paper presents a new technique for classifying electrical power quality disturbance events based on a novel Self-Adapting Artificial Neural Network (SAANN), which has the unique capability of adapting to new disturbances. A PhD project (J. V. Wijayakulasooriya) funded by the University studentship. |
| Uncontrolled Keywords: | computer simulation, discrete wavelet transform, fast Fourier transform, feature vectors |
| Subjects: | H600 Electronic and Electrical Engineering |
| Department: | Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering |
| Depositing User: | EPrint Services |
| Date Deposited: | 26 Nov 2008 14:06 |
| Last Modified: | 17 Dec 2023 16:02 |
| URI: | https://nrl.northumbria.ac.uk/id/eprint/344 |
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