Multilayer perceptron with local constraint as an emerging method in spatial data analysis
Details
Serval ID
serval:BIB_0D845F3DC4FF
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Multilayer perceptron with local constraint as an emerging method in spatial data analysis
Journal
Nuclear Instruments and Methods in Physics Research Section A - Accelerators, Spectrometers, Detectors, and Associated Equipment
ISSN-L
0168-9002
Publication state
Published
Issued date
1997
Peer-reviewed
Oui
Volume
389
Pages
226-229
Language
english
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
Abstract
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.
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.
Create date
07/10/2012 15:53
Last modification date
20/08/2019 12:34
Usage data
