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Title:
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A New Learning Algorithm for the Fuzzy Adaptive Resonance Theory: Multispectral Classification of the Algierss Bay |
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Author(s):
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Farid Alilat , Saliha Loumi , Boualem Sansal |
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ISBN:
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ISSN: 1646-3692 |
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Editors:
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Mohammad Essaaidi and Mohammed El Mohajir (Guest Editors) |
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Year:
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2009 |
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Edition:
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V IV, 1 |
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Keywords:
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Neural Networks, fuzzy ART, fuzzy ARTMAP, Remote sensing,
Multispectral classification |
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Type:
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Journal Paper |
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First Page:
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42 |
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Last Page:
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53 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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This paper presents a new learning algorithm for the fuzzy adaptive resonance theory.
The modification allows us to supervise the fuzzy ART and to simplify ARTMAP
network. It consists to find networks parameters (comparison, training and vigilance)
which gave the minimum quadratic distances between the output of the training base
and those obtained by the network. A comparative study of these two parameterized
network and an third modified fuzzy ARTMAP are done. In this last network, learning
is done differently. We dont take account of the eight (08) values of networks
parameters. As application we carried out a classification of the image of Algierss bay
taken by SPOT XS. The results of this study presented in the forms of curves, tables
and images show that modified fuzzy ARTMAP presents the best compromise
quality/computing time. |
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