Flood forecasting at Kinabatangan River, Sabah by utilizing artificial neural network (ann)

Flood event is among the most influential disaster in Malaysia .Therefore, the developing of flood forecasting model is to minimize the effects of flood and to achieve a model with high accuracy by utilizing Artificial Neural Network (ANN). Artificial Neural Network is a highly non-linear and can ca...

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Main Author:	Wan Nurul Hafizah, Abd Razak
Format:	Undergraduates Project Papers
Language:	English English English
Published:	2015
Subjects:	TA Engineering (General). Civil engineering (General)
Online Access:	http://umpir.ump.edu.my/id/eprint/11933/ http://umpir.ump.edu.my/id/eprint/11933/ http://umpir.ump.edu.my/id/eprint/11933/1/FSSKA-%20WAN%20NURULHAFIZAH%20BT%20ABD%20RAZAK%20%289330%29.pdf http://umpir.ump.edu.my/id/eprint/11933/7/FSSKA-%20WAN%20NURULHAFIZAH%20BT%20ABD%20RAZAK%20%289330%29%20-%20CHAP%201.pdf http://umpir.ump.edu.my/id/eprint/11933/8/FSSKA-%20WAN%20NURULHAFIZAH%20BT%20ABD%20RAZAK%20%289330%29%20-%20CHAP%203.pdf

id	ump-11933
recordtype	eprints
spelling	ump-119332016-03-15T02:28:38Z http://umpir.ump.edu.my/id/eprint/11933/ Flood forecasting at Kinabatangan River, Sabah by utilizing artificial neural network (ann) Wan Nurul Hafizah, Abd Razak TA Engineering (General). Civil engineering (General) Flood event is among the most influential disaster in Malaysia .Therefore, the developing of flood forecasting model is to minimize the effects of flood and to achieve a model with high accuracy by utilizing Artificial Neural Network (ANN). Artificial Neural Network is a highly non-linear and can capture the complex interactions among input variables in a system without any prior knowledge about the nature of these interactions. Nowadays, ANN is widely used in prediction and forecasting in water resources. The area of study the flood forecasting is carried out at the Balat Station, Kinabatangan River, Sabah where the hourly water level data is collected from Department of Irrigation and Drainage (DID) from year 2000 until 2014. The results indicated that the model develop a highest accuracy is 6 hour time interval for 4000 iteration where the NSC result is 0.996 with lower RMSE 155.341 compared to others iteration and time interval. This modal achieved 100% at allowable error less than 500 mm which is show the prediction of water level. As a conclusion, this model shows high accuracy and water level can be used alone. This can be applied in the real world to give out warning on imminent flood. 2015-06 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/11933/1/FSSKA-%20WAN%20NURULHAFIZAH%20BT%20ABD%20RAZAK%20%289330%29.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/11933/7/FSSKA-%20WAN%20NURULHAFIZAH%20BT%20ABD%20RAZAK%20%289330%29%20-%20CHAP%201.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/11933/8/FSSKA-%20WAN%20NURULHAFIZAH%20BT%20ABD%20RAZAK%20%289330%29%20-%20CHAP%203.pdf Wan Nurul Hafizah, Abd Razak (2015) Flood forecasting at Kinabatangan River, Sabah by utilizing artificial neural network (ann). Faculty of Civil Engineering & Earth Resources, Universiti Malaysia Pahang. http://iportal.ump.edu.my/lib/item?id=chamo:92263&theme=UMP2
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English English English
topic	TA Engineering (General). Civil engineering (General)
spellingShingle	TA Engineering (General). Civil engineering (General) Wan Nurul Hafizah, Abd Razak Flood forecasting at Kinabatangan River, Sabah by utilizing artificial neural network (ann)
description	Flood event is among the most influential disaster in Malaysia .Therefore, the developing of flood forecasting model is to minimize the effects of flood and to achieve a model with high accuracy by utilizing Artificial Neural Network (ANN). Artificial Neural Network is a highly non-linear and can capture the complex interactions among input variables in a system without any prior knowledge about the nature of these interactions. Nowadays, ANN is widely used in prediction and forecasting in water resources. The area of study the flood forecasting is carried out at the Balat Station, Kinabatangan River, Sabah where the hourly water level data is collected from Department of Irrigation and Drainage (DID) from year 2000 until 2014. The results indicated that the model develop a highest accuracy is 6 hour time interval for 4000 iteration where the NSC result is 0.996 with lower RMSE 155.341 compared to others iteration and time interval. This modal achieved 100% at allowable error less than 500 mm which is show the prediction of water level. As a conclusion, this model shows high accuracy and water level can be used alone. This can be applied in the real world to give out warning on imminent flood.
format	Undergraduates Project Papers
author	Wan Nurul Hafizah, Abd Razak
author_facet	Wan Nurul Hafizah, Abd Razak
author_sort	Wan Nurul Hafizah, Abd Razak
title	Flood forecasting at Kinabatangan River, Sabah by utilizing artificial neural network (ann)
title_short	Flood forecasting at Kinabatangan River, Sabah by utilizing artificial neural network (ann)
title_full	Flood forecasting at Kinabatangan River, Sabah by utilizing artificial neural network (ann)
title_fullStr	Flood forecasting at Kinabatangan River, Sabah by utilizing artificial neural network (ann)
title_full_unstemmed	Flood forecasting at Kinabatangan River, Sabah by utilizing artificial neural network (ann)
title_sort	flood forecasting at kinabatangan river, sabah by utilizing artificial neural network (ann)
publishDate	2015
url	http://umpir.ump.edu.my/id/eprint/11933/ http://umpir.ump.edu.my/id/eprint/11933/ http://umpir.ump.edu.my/id/eprint/11933/1/FSSKA-%20WAN%20NURULHAFIZAH%20BT%20ABD%20RAZAK%20%289330%29.pdf http://umpir.ump.edu.my/id/eprint/11933/7/FSSKA-%20WAN%20NURULHAFIZAH%20BT%20ABD%20RAZAK%20%289330%29%20-%20CHAP%201.pdf http://umpir.ump.edu.my/id/eprint/11933/8/FSSKA-%20WAN%20NURULHAFIZAH%20BT%20ABD%20RAZAK%20%289330%29%20-%20CHAP%203.pdf
first_indexed	2023-09-18T22:13:01Z
last_indexed	2023-09-18T22:13:01Z
_version_	1777415153303683072

Flood forecasting at Kinabatangan River, Sabah by utilizing artificial neural network (ann)

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