Abstract: Power Quality is defined as the study of the quality of electric power lines. The detection and classification of the different disturbances which cause power quality problems is a difficult task which requires a high level of engineering expertise. Thus, neural networks are usually a good choice for the detection and classification of these disturbances. This paper describes a powerful tool, developed by the Institute for Natural Resources and Agrobiology at the Scientific Research Council (CSIC) and the Electronic Technology Department at the University of Seville, which generates electrical patterns of disturbances for the training of neural networks for PQ tasks.
Authors: Iñigo Monedero, José Luis de la Vega, Carlos León, Juan C. Montaño, José Manuel Elena.
Paper in Artificial Intelligence Applications (International) in Innsbruck, Austria at February, 2004.
Publication: IASTED INTERNATIONAL CONFERENCE ARTIFICIAL INTELLIGENCE AND APPLICATIONS.
ISBN: 0-88986-352-0
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