Water level forecasting using artificial neural network in sungai Pahang, Temerloh

Flood forecasting models are a necessity, as they help in planning for flood events, and thus help prevent loss of lives and minimize damage. Current studies have shown that artificial neural networks (ANN) which is a parallel computing model have been successfully applied in water level forecasting...

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Main Author:	Ainul Afifah, Zakaria
Format:	Undergraduates Project Papers
Language:	English
Published:	2014
Subjects:	GB Physical geography
Online Access:	http://umpir.ump.edu.my/id/eprint/10211/ http://umpir.ump.edu.my/id/eprint/10211/ http://umpir.ump.edu.my/id/eprint/10211/1/AINUL%20AFIFAH%20BINTI%20ZAKARIA.PDF

id	ump-10211
recordtype	eprints
spelling	ump-102112015-09-10T07:07:35Z http://umpir.ump.edu.my/id/eprint/10211/ Water level forecasting using artificial neural network in sungai Pahang, Temerloh Ainul Afifah, Zakaria GB Physical geography Flood forecasting models are a necessity, as they help in planning for flood events, and thus help prevent loss of lives and minimize damage. Current studies have shown that artificial neural networks (ANN) which is a parallel computing model have been successfully applied in water level forecasting studies. (ANN) models require historical data of the subject being study. This data is normally separated into a training dataset and a validation dataset. Several performance measures such as Nash-Sutcliffe efficiency, root mean square error and error distribution are used to evaluate forecasting results. BASIC256 software and Microsoft Excel are other way used to implement to ANN modelling technique. The daily water level data can be taken from the Department of Irrigation and Drainage (DID), Malaysia. Water level forecasting is important for environmental protection and flood control since, when flood events occur, reliable water level forecasts enable the early warning systems to mitigate the flood effects. Importantly, the forecasting model developed based on (ANN) successfully achieves high accuracy forecasting result and satisfactory performance result. 2014 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/10211/1/AINUL%20AFIFAH%20BINTI%20ZAKARIA.PDF Ainul Afifah, Zakaria (2014) Water level forecasting using artificial neural network in sungai Pahang, Temerloh. Faculty of Civil Engineering and Earth Resources, Universiti Malaysia Pahang. http://iportal.ump.edu.my/lib/item?id=chamo:84678&theme=UMP2
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	GB Physical geography
spellingShingle	GB Physical geography Ainul Afifah, Zakaria Water level forecasting using artificial neural network in sungai Pahang, Temerloh
description	Flood forecasting models are a necessity, as they help in planning for flood events, and thus help prevent loss of lives and minimize damage. Current studies have shown that artificial neural networks (ANN) which is a parallel computing model have been successfully applied in water level forecasting studies. (ANN) models require historical data of the subject being study. This data is normally separated into a training dataset and a validation dataset. Several performance measures such as Nash-Sutcliffe efficiency, root mean square error and error distribution are used to evaluate forecasting results. BASIC256 software and Microsoft Excel are other way used to implement to ANN modelling technique. The daily water level data can be taken from the Department of Irrigation and Drainage (DID), Malaysia. Water level forecasting is important for environmental protection and flood control since, when flood events occur, reliable water level forecasts enable the early warning systems to mitigate the flood effects. Importantly, the forecasting model developed based on (ANN) successfully achieves high accuracy forecasting result and satisfactory performance result.
format	Undergraduates Project Papers
author	Ainul Afifah, Zakaria
author_facet	Ainul Afifah, Zakaria
author_sort	Ainul Afifah, Zakaria
title	Water level forecasting using artificial neural network in sungai Pahang, Temerloh
title_short	Water level forecasting using artificial neural network in sungai Pahang, Temerloh
title_full	Water level forecasting using artificial neural network in sungai Pahang, Temerloh
title_fullStr	Water level forecasting using artificial neural network in sungai Pahang, Temerloh
title_full_unstemmed	Water level forecasting using artificial neural network in sungai Pahang, Temerloh
title_sort	water level forecasting using artificial neural network in sungai pahang, temerloh
publishDate	2014
url	http://umpir.ump.edu.my/id/eprint/10211/ http://umpir.ump.edu.my/id/eprint/10211/ http://umpir.ump.edu.my/id/eprint/10211/1/AINUL%20AFIFAH%20BINTI%20ZAKARIA.PDF
first_indexed	2023-09-18T22:09:35Z
last_indexed	2023-09-18T22:09:35Z
_version_	1777414937113526272

Water level forecasting using artificial neural network in sungai Pahang, Temerloh

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