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Application of neural networks to predict ice jam occurrence

Author
MASSIE, Darrell D1 ; WHITE, Kathleen D2 ; DALY, Steven F2
[1] Department of Civil and Mechanical Engineering, United States Military Academy, West Point, NY 10996, United States
[2] US Army Engineer Research and Development Center, Cold Regions Research and Engineering Laboratory, 72 Lyme Road, Hanover, NH 03755, United States
Source

Cold regions science and technology. 2002, Vol 35, Num 2, pp 115-122 ; Illustration , Table ; ref : 8 ref

CODEN
CRSTDL
ISSN
0165-232X
Scientific domain
Environment; Civil engineering; Geology; Geophysics
Publisher
Elsevier, Amsterdam
Publication country
Netherlands
Document type
Article
Language
English
Keyword (fr)
Analyse statistique Classification Crue Débit rivière Glace Intelligence artificielle Modèle Prévision Régression statistique Réseau neuronal Embâcle Pennsylvanie Amérique du Nord Etats Unis
Keyword (en)
statistical analysis classification floods river discharge ice artificial intelligence models prediction regression analysis neural networks Pennsylvania North America United States
Keyword (es)
Clasificación Crecida Caudal río Hielo Modelo Previsión Regresión estadística Red neuronal Pensilvania America del norte Estados Unidos
Classification
Pascal
001 Exact sciences and technology / 001E Earth, ocean, space / 001E01 Earth sciences / 001E01N Hydrology. Hydrogeology / 001E01N01 Hydrology

Discipline
Earth sciences
Origin
Inist-CNRS
Database
PASCAL
INIST identifier
13851314

Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS

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