DocumentCode
1458661
Title
Neural networks´ power
Author
El-Sharkawi, M.A.
Author_Institution
Dept. of Electr. Eng., Washington Univ., USA
Volume
15
Issue
5
fYear
1997
Firstpage
12
Lastpage
15
Abstract
Neural networks (NNs) are effective systems for learning pattern discriminants from a body of examples. Artificial neural networks (ANNs) have been developed in a wide variety of configurations with some common underlying characteristics. All ANNs attempt to achieve good performance via massive interconnection of simple computational elements. Neural networks are characterized by the model of their neurons, the connections among them and the methods used to train them to do specific tasks. The author describes multi-layer neural networks and Kohonen neural networks. The author then discusses how they are used in electric load forecasting and power system security assessment
Keywords
load forecasting; multilayer perceptrons; power system analysis computing; power system security; self-organising feature maps; Kohonen neural networks; artificial neural networks; computational elements interconnection; electric load forecasting; multi-layer neural networks; neurons training; pattern discriminants learning; power system security assessment; Artificial neural networks; Computer networks; Hopfield neural networks; Load forecasting; Multi-layer neural network; Neural networks; Neurons; Power system harmonics; Power system security; Speech recognition;
fLanguage
English
Journal_Title
Potentials, IEEE
Publisher
ieee
ISSN
0278-6648
Type
jour
DOI
10.1109/45.544033
Filename
544033
Link To Document