Technical note: Application of artificial neural networks in groundwater table forecasting-a case study in a Singapore swamp forest

10.5194/hess-20-1405-2016

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Bibliographic Details
Main Authors:	Sun, Y, Wendi, D, Kim, D.E, Liong, S.-Y
Other Authors:	TROPICAL MARINE SCIENCE INSTITUTE
Format:	Article
Published:	2020
Subjects:	Forestry Groundwater Groundwater resources Neural networks Reservoirs (water) Wetlands Accurate prediction Computational costs Efficient managements Ground water table Hydrological regime Parameter uncertainty Physical parameters Physical systems Forecasting artificial neural network forecasting method groundwater groundwater resource hydrological regime numerical model performance assessment reservoir swamp forest water table Singapore [Southeast Asia]
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/176131
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Institution:	National University of Singapore

id	sg-nus-scholar.10635-176131
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spelling	sg-nus-scholar.10635-1761312024-11-14T18:00:43Z Technical note: Application of artificial neural networks in groundwater table forecasting-a case study in a Singapore swamp forest Sun, Y Wendi, D Kim, D.E Liong, S.-Y TROPICAL MARINE SCIENCE INSTITUTE Forestry Groundwater Groundwater resources Neural networks Reservoirs (water) Wetlands Accurate prediction Computational costs Efficient managements Ground water table Hydrological regime Parameter uncertainty Physical parameters Physical systems Forecasting artificial neural network forecasting method groundwater groundwater resource hydrological regime numerical model performance assessment reservoir swamp forest water table Singapore [Southeast Asia] 10.5194/hess-20-1405-2016 Hydrology and Earth System Sciences 20 4 1405-1412 2020-09-14T08:14:06Z 2020-09-14T08:14:06Z 2016 Article Sun, Y, Wendi, D, Kim, D.E, Liong, S.-Y (2016). Technical note: Application of artificial neural networks in groundwater table forecasting-a case study in a Singapore swamp forest. Hydrology and Earth System Sciences 20 (4) : 1405-1412. ScholarBank@NUS Repository. https://doi.org/10.5194/hess-20-1405-2016 1027-5606 https://scholarbank.nus.edu.sg/handle/10635/176131 Unpaywall 20200831
institution	National University of Singapore
building	NUS Library
continent	Asia
country	Singapore Singapore
content_provider	NUS Library
collection	ScholarBank@NUS
topic	Forestry Groundwater Groundwater resources Neural networks Reservoirs (water) Wetlands Accurate prediction Computational costs Efficient managements Ground water table Hydrological regime Parameter uncertainty Physical parameters Physical systems Forecasting artificial neural network forecasting method groundwater groundwater resource hydrological regime numerical model performance assessment reservoir swamp forest water table Singapore [Southeast Asia]
spellingShingle	Forestry Groundwater Groundwater resources Neural networks Reservoirs (water) Wetlands Accurate prediction Computational costs Efficient managements Ground water table Hydrological regime Parameter uncertainty Physical parameters Physical systems Forecasting artificial neural network forecasting method groundwater groundwater resource hydrological regime numerical model performance assessment reservoir swamp forest water table Singapore [Southeast Asia] Sun, Y Wendi, D Kim, D.E Liong, S.-Y Technical note: Application of artificial neural networks in groundwater table forecasting-a case study in a Singapore swamp forest
description	10.5194/hess-20-1405-2016
author2	TROPICAL MARINE SCIENCE INSTITUTE
author_facet	TROPICAL MARINE SCIENCE INSTITUTE Sun, Y Wendi, D Kim, D.E Liong, S.-Y
format	Article
author	Sun, Y Wendi, D Kim, D.E Liong, S.-Y
author_sort	Sun, Y
title	Technical note: Application of artificial neural networks in groundwater table forecasting-a case study in a Singapore swamp forest
title_short	Technical note: Application of artificial neural networks in groundwater table forecasting-a case study in a Singapore swamp forest
title_full	Technical note: Application of artificial neural networks in groundwater table forecasting-a case study in a Singapore swamp forest
title_fullStr	Technical note: Application of artificial neural networks in groundwater table forecasting-a case study in a Singapore swamp forest
title_full_unstemmed	Technical note: Application of artificial neural networks in groundwater table forecasting-a case study in a Singapore swamp forest
title_sort	technical note: application of artificial neural networks in groundwater table forecasting-a case study in a singapore swamp forest
publishDate	2020
url	https://scholarbank.nus.edu.sg/handle/10635/176131
_version_	1821228376656969728

Technical note: Application of artificial neural networks in groundwater table forecasting-a case study in a Singapore swamp forest

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