Prospective Interest of Deep Learning for Hydrological Inference
Ground Water
.
2017 Sep;55(5):688-692.
doi: 10.1111/gwat.12557.
Epub 2017 Jul 21.
Authors
Jean Marçais
1
2
,
Jean-Raynald de Dreuzy
2
Affiliations
1
AgroParisTech, 16 Rue Claude Bernard, 75005 Paris, France.
2
Géosciences Rennes, Université de Rennes 1, 35042 Rennes Cedex, France.
PMID:
28732108
DOI:
10.1111/gwat.12557
No abstract available
Publication types
Comment
MeSH terms
Algorithms
Association Learning
Environmental Monitoring
Groundwater*
Humans
Hydrology
Learning*
Machine Learning
Models, Theoretical
Prospective Studies