Wavelet decomposition-NNARX model for flood prediction of Kelantan River, Malaysia

Flood is a major disaster that happens around the world. It has caused the loss of many precious lives and massive destruction of property. The possibility of flood can be determined depends on many factors that consist of rainfall, structure of the river, flow rate of the river et...

全面介紹

Saved in:
書目詳細資料
主要作者: Anuar, Mohd Azrol Syafiee
格式: Thesis
語言:English
出版: 2018
主題:
在線閱讀:http://psasir.upm.edu.my/id/eprint/84219/1/FK%202019%2095%20-%20ir.pdf
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
id my-upm-ir.84219
record_format uketd_dc
spelling my-upm-ir.842192022-01-04T02:27:53Z Wavelet decomposition-NNARX model for flood prediction of Kelantan River, Malaysia 2018-12-23 Anuar, Mohd Azrol Syafiee Flood is a major disaster that happens around the world. It has caused the loss of many precious lives and massive destruction of property. The possibility of flood can be determined depends on many factors that consist of rainfall, structure of the river, flow rate of the river etc. One of the research challenges is to develop accurate prediction models and what improvement can be made to the forecasting model. The objective of this thesis is to improve the performance of the neural network model to predict the flood on the Kelantan River, Malaysia. A technique for modelling of nonlinear data of flood forecasting using wavelet decomposition-neural network autoregressive exogenous input (NNARX) approach is proposed. This thesis discusses the identification of parameters that involved in the forecasting field as rainfall value, flow rate of the river and the river water level. With the original data acquired, the data had been processing through to wavelet decomposition and filtered to generate a new set of input data for NNARX prediction model. This proposed technique has been compared with the non-wavelet NNARX. The experimental result show that the proposed approach provides better testing performance compared to its counterpart, which the mean square error obtained is 2.0491e⁻⁴ while the normal NNARX is 6.1642e⁻⁴. Wavelets (Mathematics) Flood prediction 2018-12 Thesis http://psasir.upm.edu.my/id/eprint/84219/ http://psasir.upm.edu.my/id/eprint/84219/1/FK%202019%2095%20-%20ir.pdf text en public masters Universiti Putra Malaysia Wavelets (Mathematics) Flood prediction Abdul Rahman, Ribhan Zafira
institution Universiti Putra Malaysia
collection PSAS Institutional Repository
language English
advisor Abdul Rahman, Ribhan Zafira
topic Wavelets (Mathematics)
Flood prediction

spellingShingle Wavelets (Mathematics)
Flood prediction

Anuar, Mohd Azrol Syafiee
Wavelet decomposition-NNARX model for flood prediction of Kelantan River, Malaysia
description Flood is a major disaster that happens around the world. It has caused the loss of many precious lives and massive destruction of property. The possibility of flood can be determined depends on many factors that consist of rainfall, structure of the river, flow rate of the river etc. One of the research challenges is to develop accurate prediction models and what improvement can be made to the forecasting model. The objective of this thesis is to improve the performance of the neural network model to predict the flood on the Kelantan River, Malaysia. A technique for modelling of nonlinear data of flood forecasting using wavelet decomposition-neural network autoregressive exogenous input (NNARX) approach is proposed. This thesis discusses the identification of parameters that involved in the forecasting field as rainfall value, flow rate of the river and the river water level. With the original data acquired, the data had been processing through to wavelet decomposition and filtered to generate a new set of input data for NNARX prediction model. This proposed technique has been compared with the non-wavelet NNARX. The experimental result show that the proposed approach provides better testing performance compared to its counterpart, which the mean square error obtained is 2.0491e⁻⁴ while the normal NNARX is 6.1642e⁻⁴.
format Thesis
qualification_level Master's degree
author Anuar, Mohd Azrol Syafiee
author_facet Anuar, Mohd Azrol Syafiee
author_sort Anuar, Mohd Azrol Syafiee
title Wavelet decomposition-NNARX model for flood prediction of Kelantan River, Malaysia
title_short Wavelet decomposition-NNARX model for flood prediction of Kelantan River, Malaysia
title_full Wavelet decomposition-NNARX model for flood prediction of Kelantan River, Malaysia
title_fullStr Wavelet decomposition-NNARX model for flood prediction of Kelantan River, Malaysia
title_full_unstemmed Wavelet decomposition-NNARX model for flood prediction of Kelantan River, Malaysia
title_sort wavelet decomposition-nnarx model for flood prediction of kelantan river, malaysia
granting_institution Universiti Putra Malaysia
publishDate 2018
url http://psasir.upm.edu.my/id/eprint/84219/1/FK%202019%2095%20-%20ir.pdf
_version_ 1747813451667865600