Please use this identifier to cite or link to this item: https://doi.org/10.1029/2019wr026933
Title: Hydrologically Informed Machine Learning for Rainfall‐Runoff Modeling: A Genetic Programming‐Based Toolkit for Automatic Model Induction
Authors: Chadalawada, Jayashree 
Herath, HMVV
Babovic, Vladan 
Issue Date: Apr-2020
Publisher: American Geophysical Union (AGU)
Citation: Chadalawada, Jayashree, Herath, HMVV, Babovic, Vladan (2020-04). Hydrologically Informed Machine Learning for Rainfall‐Runoff Modeling: A Genetic Programming‐Based Toolkit for Automatic Model Induction. Water Resources Research 56 (4). ScholarBank@NUS Repository. https://doi.org/10.1029/2019wr026933
Source Title: Water Resources Research
URI: https://scholarbank.nus.edu.sg/handle/10635/166568
ISSN: 0043-1397,1944-7973
DOI: 10.1029/2019wr026933
Appears in Collections:Staff Publications
Elements

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
2019WR026933.pdf16.88 MBAdobe PDF

OPEN

PublishedView/Download

SCOPUSTM   
Citations

6
checked on Jun 19, 2021

Page view(s)

109
checked on Jun 11, 2021

Download(s)

4
checked on Jun 11, 2021

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.