@article{62313e21775d462b8a84ffd5fe745c88,
title = "Electric power quality disturbance classification using self-adapting artificial neural networks",
keywords = "computer simulation, discrete wavelet transform, fast Fourier transform, feature vectors",
author = "Wijayakulasooriya, \{Janaka V.\} and Ghanim Putrus and Peter Minns",
note = "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.",
year = "2002",
month = jan,
doi = "10.1049/ip-gtd:20020014",
language = "English",
volume = "149",
pages = "98",
journal = "IEE Proceedings: Generation, Transmission and Distribution",
issn = "1350-2360",
publisher = "Blackwell Publishing",
number = "1",
}