ScienceOpen:
research and publishing network
For Publishers
Discovery
Metadata
Peer review
Hosting
Publishing
For Researchers
Join
Publish
Review
Collect
My ScienceOpen
Sign in
Register
Dashboard
Blog
About
Search
Advanced search
My ScienceOpen
Sign in
Register
Dashboard
Search
Search
Advanced search
For Publishers
Discovery
Metadata
Peer review
Hosting
Publishing
For Researchers
Join
Publish
Review
Collect
Blog
About
15
views
26
references
Top references
cited by
113
Cite as...
0 reviews
Review
0
comments
Comment
0
recommends
+1
Recommend
0
collections
Add to
0
shares
Share
Twitter
Sina Weibo
Facebook
Email
2,593
similar
All similar
Record
: found
Abstract
: not found
Article
: not found
A comparative study of artificial neural networks and support vector machines for predicting groundwater levels in a coastal aquifer
Author(s):
Heesung Yoon
,
Seong-Chun Jun
,
Yunjung Hyun
,
Gwang-Ok Bae
,
Kang-Kun Lee
Publication date
Created:
January 2011
Publication date
(Print):
January 2011
Journal:
Journal of Hydrology
Publisher:
Elsevier BV
Read this article at
ScienceOpen
Publisher
Review
Review article
Invite someone to review
Bookmark
Cite as...
There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.
Related collections
Vector Biology
Most cited references
26
Record
: found
Abstract
: not found
Article
: not found
Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology
Keith J Beven
,
Jim Freer
(2001)
0
comments
Cited
380
times
– based on
0
reviews
Review now
Bookmark
Record
: found
Abstract
: not found
Article
: not found
Neural networks for the prediction and forecasting of water resources variables: a review of modelling issues and applications
Graeme Dandy
,
Holger Maier
(2000)
0
comments
Cited
352
times
– based on
0
reviews
Review now
Bookmark
Record
: found
Abstract
: not found
Article
: not found
Support vector regression for real-time flood stage forecasting
Pao-Shan Yu
,
I-Fan Chang
,
Shien-Tsung Chen
(2006)
0
comments
Cited
112
times
– based on
0
reviews
Review now
Bookmark
All references
Author and article information
Journal
Title:
Journal of Hydrology
Abbreviated Title:
Journal of Hydrology
Publisher:
Elsevier BV
ISSN (Print):
00221694
Publication date Created:
January 2011
Publication date (Print):
January 2011
Volume
: 396
Issue
: 1-2
Pages
: 128-138
Article
DOI:
10.1016/j.jhydrol.2010.11.002
SO-VID:
536f882e-632f-41b5-99d1-e019963dac92
Copyright ©
© 2011
License:
http://www.elsevier.com/tdm/userlicense/1.0/
History
Data availability:
Comments
Comment on this article
Sign in to comment
scite_
Similar content
2,593
Biodegradation of three selected benzotriazoles in aquifer materials under aerobic and anaerobic conditions.
Authors:
You-Sheng Liu
,
Guang-Guo Ying
,
Ali Shareef
…
In-situ biodegradation of tetrachloroethene and trichloroethene in contaminated aquifers monitored by stable isotope fractionation.
Authors:
A Vieth
,
J Müller
,
G Strauch
…
E v aluation of intrinsic vulnerability against seawater intrusion using the GALDIT approach . A pplication to the R’mel aquifer (North W est of Morocco)
Authors:
H. Cherkaoui Dekkaki
,
M Ben Ali
,
A. Ait Taleb
…
See all similar
Cited by
113
A Transdisciplinary Review of Deep Learning Research and Its Relevance for Water Resources Scientists
Authors:
Chaopeng Shen
Machine learning algorithms for modeling groundwater level changes in agricultural regions of the U.S.
Authors:
S. Sahoo
,
T Russo
,
I Foster
…
Extreme gradient boosting (Xgboost) model to predict the groundwater levels in Selangor Malaysia
Authors:
Ahmedbahaaaldin Ibrahem Ahmed Osman
,
Ali Najah Ahmed
,
Ming Fai Chow
…
See all cited by
Most referenced authors
238
S. SINGH
S Yu
S. S. Singh
See all reference authors