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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Saikia, L.C. Borah, S.M. Pait, S. |
| Copyright Year | 2010 |
| Description | Author affiliation: Electrical Engineering Department, National Institute of Technology Silchar, Assam, India (Saikia, L.C.; Borah, S.M.; Pait, S.) |
| Abstract | This paper presents an approach for detection and classification of power quality disturbances using wavelet transform, fuzzy logic and neural network. The total harmonic distortion (THD) and energy of the disturb signals are used for classification. A maiden attempt is made to apply a new tool called neuro solution for artificial neural network (ANN) in the field of power quality disturbance classification. A comparison of fuzzy logic and neural network for disturbance classification has been made. Comparison of these two techniques reveals that ANN is more accurate and efficient than the fuzzy logic. |
| Starting Page | 1 |
| Ending Page | 5 |
| File Size | 357644 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424490721 |
| e-ISBN | 9781424490745 |
| DOI | 10.1109/INDCON.2010.5712674 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-12-17 |
| Publisher Place | India |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Wavelet transforms Fuzzy logic Nerve fibers Artificial Neural Network Power quality power quality Artificial neural networks wavelet transform fuzzy logic Wavelet analysis |
| Content Type | Text |
| Resource Type | Article |
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