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  • Feature Reduction for Neural Network based Small-Signal Stability Assessment

Feature Reduction for Neural Network based Small-Signal Stability Assessment

Affiliation
University of Duisburg, Germany
Teeuwsen, Simon Patrick;
GND
121269192X
Affiliation
University of Duisburg, Germany
Erlich, István;
GND
1099328977
Affiliation
University of Washington, Seattle, USA
El-Sharkawi, Mohamed A.
This paper introduces several feature extraction and selection techniques.Previous studies showed good results when neural networks are applied to the small-signal stability assessment. However the use of reduction techniques can decrease the number of features and thus the number of quantities, which need to be observed, measured and transmitted, respectively.

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Conference:
14th Power System Computation Conference, PSCC 02, Sevilla, Spanien, 24.-28. Juni 2002
Date Issued:
2002
URN:
urn:nbn:de:hbz:464-20120718-143256-1
PURL:
http://purl.oclc.org/NET/duett-04142003-142255
Language:
English
Type of Resource:
Text
Keywords:
Clustering; Principal Components; Feature extraction; Neural network; Small-signal stability
Collection:
E-Publications
Dewey Decimal Classification:
620 Engineering
Subject categories of the Deutsche Nationalbibliografie:
620 Engineering & allied operations
Hosting institution:
Faculty of Engineering, Engineering and Information Technology
Info on primary publication:

Teeuwsen, Simon Patrick/Erlich, István/El-Sharkawi, Mohamed A.: Feature Reduction for Neural Network based Small-Signal Stability Assessment.

In: 14th Power System Computation Conference, PSCC 02, Sevilla, Spanien, 24.-28. Juni 2002. Session 14, Paper 4.

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