Prediction of Temerloh River water level for prediction of flood using Artificial Neural Network (ANN) method

The purpose of this project is to research more about the flood occurrence in Temerloh, Pahang. The data mining approaches using artificial neural network (ANN) techniques will be use to conduct this research for flood estimation. ANN model will be use to estimate river water level by taking present...

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Main Author:	Muhamad Afiq, Mustafa
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/12252/ http://umpir.ump.edu.my/id/eprint/12252/ http://umpir.ump.edu.my/id/eprint/12252/1/FKASA%20-%20MUHAMAD%20AFIQ%20MUSTAFA%20%28CD9276%29.pdf http://umpir.ump.edu.my/id/eprint/12252/2/FKASA%20-%20MUHAMAD%20AFIQ%20MUSTAFA%20%28CD9276%29%20-%20CHAP%201.pdf http://umpir.ump.edu.my/id/eprint/12252/3/FKASA%20-%20MUHAMAD%20AFIQ%20MUSTAFA%20%28CD9276%29%20-%20CHAP%203.pdf

id	ump-12252
recordtype	eprints
spelling	ump-122522016-03-17T07:08:53Z http://umpir.ump.edu.my/id/eprint/12252/ Prediction of Temerloh River water level for prediction of flood using Artificial Neural Network (ANN) method Muhamad Afiq, Mustafa TA Engineering (General). Civil engineering (General) The purpose of this project is to research more about the flood occurrence in Temerloh, Pahang. The data mining approaches using artificial neural network (ANN) techniques will be use to conduct this research for flood estimation. ANN model will be use to estimate river water level by taking present river water level data. The research will be trained using back propagation method to estimate the flood water level at Temerloh River. ANN’s trained using backpropagation are also known as “feed forward multilayered networks” trained using the backpropagation algorithm. 14 years of rainfall data is get from Department of irrigation and drainage (DID). Rainfall data of 10 years(2000-2010) will be training data to predict the others 4 years(2010-2014) river water level using python software with 1000-4000 iteration of data. At the end of the project we can make parameter model that can use as a tools to predict accurately water level data and achieve high accuracy of flood forecasting. From the result we can see that in this research the best prediction for water level data at Temerloh River is 3-hr lead-time with 6 input 1 output in 4000 iteration because it produce the best CE with 0.998.The average RMSE also less than 500 mm with only small difference error in percentage. 2015-06 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/12252/1/FKASA%20-%20MUHAMAD%20AFIQ%20MUSTAFA%20%28CD9276%29.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/12252/2/FKASA%20-%20MUHAMAD%20AFIQ%20MUSTAFA%20%28CD9276%29%20-%20CHAP%201.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/12252/3/FKASA%20-%20MUHAMAD%20AFIQ%20MUSTAFA%20%28CD9276%29%20-%20CHAP%203.pdf Muhamad Afiq, Mustafa (2015) Prediction of Temerloh River water level for prediction of flood using Artificial Neural Network (ANN) method. Faculty of Civil Engineering & Earth Resources, Universiti Malaysia Pahang. http://iportal.ump.edu.my/lib/item?id=chamo:92187&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) Muhamad Afiq, Mustafa Prediction of Temerloh River water level for prediction of flood using Artificial Neural Network (ANN) method
description	The purpose of this project is to research more about the flood occurrence in Temerloh, Pahang. The data mining approaches using artificial neural network (ANN) techniques will be use to conduct this research for flood estimation. ANN model will be use to estimate river water level by taking present river water level data. The research will be trained using back propagation method to estimate the flood water level at Temerloh River. ANN’s trained using backpropagation are also known as “feed forward multilayered networks” trained using the backpropagation algorithm. 14 years of rainfall data is get from Department of irrigation and drainage (DID). Rainfall data of 10 years(2000-2010) will be training data to predict the others 4 years(2010-2014) river water level using python software with 1000-4000 iteration of data. At the end of the project we can make parameter model that can use as a tools to predict accurately water level data and achieve high accuracy of flood forecasting. From the result we can see that in this research the best prediction for water level data at Temerloh River is 3-hr lead-time with 6 input 1 output in 4000 iteration because it produce the best CE with 0.998.The average RMSE also less than 500 mm with only small difference error in percentage.
format	Undergraduates Project Papers
author	Muhamad Afiq, Mustafa
author_facet	Muhamad Afiq, Mustafa
author_sort	Muhamad Afiq, Mustafa
title	Prediction of Temerloh River water level for prediction of flood using Artificial Neural Network (ANN) method
title_short	Prediction of Temerloh River water level for prediction of flood using Artificial Neural Network (ANN) method
title_full	Prediction of Temerloh River water level for prediction of flood using Artificial Neural Network (ANN) method
title_fullStr	Prediction of Temerloh River water level for prediction of flood using Artificial Neural Network (ANN) method
title_full_unstemmed	Prediction of Temerloh River water level for prediction of flood using Artificial Neural Network (ANN) method
title_sort	prediction of temerloh river water level for prediction of flood using artificial neural network (ann) method
publishDate	2015
url	http://umpir.ump.edu.my/id/eprint/12252/ http://umpir.ump.edu.my/id/eprint/12252/ http://umpir.ump.edu.my/id/eprint/12252/1/FKASA%20-%20MUHAMAD%20AFIQ%20MUSTAFA%20%28CD9276%29.pdf http://umpir.ump.edu.my/id/eprint/12252/2/FKASA%20-%20MUHAMAD%20AFIQ%20MUSTAFA%20%28CD9276%29%20-%20CHAP%201.pdf http://umpir.ump.edu.my/id/eprint/12252/3/FKASA%20-%20MUHAMAD%20AFIQ%20MUSTAFA%20%28CD9276%29%20-%20CHAP%203.pdf
first_indexed	2023-09-18T22:13:43Z
last_indexed	2023-09-18T22:13:43Z
_version_	1777415197180297216

Prediction of Temerloh River water level for prediction of flood using Artificial Neural Network (ANN) method

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