Multilayer perceptron with local constraint as an emerging method in spatial data analysis

Détails

ID Serval
serval:BIB_0D845F3DC4FF
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Multilayer perceptron with local constraint as an emerging method in spatial data analysis
Périodique
Nuclear Instruments and Methods in Physics Research Section A - Accelerators, Spectrometers, Detectors, and Associated Equipment
Auteur(s)
De Bollivier M., Dubois G., Maignan M., Kanevski M.
ISSN-L
0168-9002
Statut éditorial
Publié
Date de publication
1997
Peer-reviewed
Oui
Volume
389
Pages
226-229
Langue
anglais
Notes
5th International Workshop on Software Engineering, Neural Nets, Genetic Algorithms, Expert Systems, Symbolic Algebra and Automatic Calculations in Physics Research (AIHENP 96), LAUSANNE, SWITZERLAND, SEP 02-06, 1996
Résumé
The use of Geographic Information Systems has revolutionalized the
handling and the visualization of geo-referenced data and has underlined
the critic role of spatial analysis. The usual tools for such a purpose
are geostatistics which are widely used in Earth science. Geostatistics
are based upon several hypothesis which are not always verified in
practice. On the other hand, Artificial Neural Network (ANN) a priori
can be used without special assumptions and are known to be flexible.
This paper proposes to discuss the application of ANN in the case of the
interpolation of a geo-referenced variable.
Création de la notice
07/10/2012 16:53
Dernière modification de la notice
03/03/2018 13:40
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