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An Example of Unsupervised Networks Kohonen's Self-Organizing Feature MapKohonen's self-organizing feature map belongs to a class of unsupervised artificial neural network commonly referred to as topographic maps. It serves two purposes, the quantization and dimensionality reduction of date. A short description of its history and its biological context is given. We show that the inherent classification properties of the feature map make it a suitable candidate for solving the classification task in power system areas like load forecasting, fault diagnosis and security assessment.
Document ID
20060037300
Acquisition Source
Jet Propulsion Laboratory
Document Type
Preprint (Draft being sent to journal)
External Source(s)
Authors
Niebur, Dagmar
Date Acquired
August 23, 2013
Publication Date
June 1, 1995
Distribution Limits
Public
Copyright
Other
Keywords
Kohonen Feature Map

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