Optimization of snowmaking in high mountains ski resort
Détails
ID Serval
serval:BIB_B286AF2AC6FD
Type
Actes de conférence (partie): contribution originale à la littérature scientifique, publiée à l'occasion de conférences scientifiques, dans un ouvrage de compte-rendu (proceedings), ou dans l'édition spéciale d'un journal reconnu (conference proceedings).
Collection
Publications
Institution
Titre
Optimization of snowmaking in high mountains ski resort
Titre de la conférence
Proceedings of the 13th AGILE International Conference on Geographic Information Science, Guimaraes, Portugal
Editeur
AGILE
ISBN
978-989-20-1953-6
Statut éditorial
Publié
Date de publication
2010
Editeur⸱rice scientifique
Painho M., Santos M.Y., Pundt H.
Pages
1-9
Langue
anglais
Résumé
Ski resorts are deploying more and more systems of artificial snow.
These tools are necessary to ensure an important economic activity
for the high alpine valleys. However, artificial snow raises important
environmental issues that can be reduced by an optimization of its
production. This paper presents a software prototype based on artificial
intelligence to help ski resorts better manage their snowpack. It
combines on one hand a General Neural Network for the analysis of
the snow cover and the spatial prediction, with on the other hand
a multiagent simulation of skiers for the analysis of the spatial
impact of ski practice. The prototype has been tested on the ski
resort of Verbier (Switzerland).
These tools are necessary to ensure an important economic activity
for the high alpine valleys. However, artificial snow raises important
environmental issues that can be reduced by an optimization of its
production. This paper presents a software prototype based on artificial
intelligence to help ski resorts better manage their snowpack. It
combines on one hand a General Neural Network for the analysis of
the snow cover and the spatial prediction, with on the other hand
a multiagent simulation of skiers for the analysis of the spatial
impact of ski practice. The prototype has been tested on the ski
resort of Verbier (Switzerland).
Mots-clé
Snowmaking, spatial prediction, multiagent simulations, General Regression, Neural Network
Création de la notice
25/11/2013 17:18
Dernière modification de la notice
20/08/2019 15:21
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