Flood frequency analysis at ungauged sites in Peninsular Malaysia using least square support vector machine

The ability of hierarchical cluster analysis (HCA) and least square support vector machine (LSSVM) in the estimation of flood quantiles at ungauged sites in Peninsular Malaysia were studied. Comparison between the multiple linear regression (MLR) models, LSSVM, HCA with MLR and HCA with LSSVM were p...

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Main Author:	Roselan, Nur Shahidah
Format:	Thesis
Published:	2014
Subjects:	GB Physical geography
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id	my-utm-ep.48452
record_format	uketd_dc
spelling	my-utm-ep.484522017-08-08T01:41:35Z Flood frequency analysis at ungauged sites in Peninsular Malaysia using least square support vector machine 2014 Roselan, Nur Shahidah GB Physical geography The ability of hierarchical cluster analysis (HCA) and least square support vector machine (LSSVM) in the estimation of flood quantiles at ungauged sites in Peninsular Malaysia were studied. Comparison between the multiple linear regression (MLR) models, LSSVM, HCA with MLR and HCA with LSSVM were performed. To assess the effectiveness of this model, 70 catchments in the province of Peninsular Malaysia with five inputs variables which namely catchment area, longest drainage area, slope of mainstream, altitude of the mainstream and mean annual rainfall were used as case studies. The performance of HCA with LSSVM was compared with the MLR, HCA with MLR and LSSVM models using various statistical measures such as relative bias (RBIAS), mean absolute relative error (MARE) and mean squared relative error (MSRE). The results of the comparison indicate that the proposed model which is HCA with LSSVM has the lowest RBIAS, MARE and MSRE compared to the other three models. This model predicts flood quantile more accurately and provides a promising alternative technique in estimation of flood quantiles in ungauged sites 2014 Thesis http://eprints.utm.my/id/eprint/48452/ masters Universiti Teknologi Malaysia, Faculty of Science Faculty of Science
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
topic	GB Physical geography
spellingShingle	GB Physical geography Roselan, Nur Shahidah Flood frequency analysis at ungauged sites in Peninsular Malaysia using least square support vector machine
description	The ability of hierarchical cluster analysis (HCA) and least square support vector machine (LSSVM) in the estimation of flood quantiles at ungauged sites in Peninsular Malaysia were studied. Comparison between the multiple linear regression (MLR) models, LSSVM, HCA with MLR and HCA with LSSVM were performed. To assess the effectiveness of this model, 70 catchments in the province of Peninsular Malaysia with five inputs variables which namely catchment area, longest drainage area, slope of mainstream, altitude of the mainstream and mean annual rainfall were used as case studies. The performance of HCA with LSSVM was compared with the MLR, HCA with MLR and LSSVM models using various statistical measures such as relative bias (RBIAS), mean absolute relative error (MARE) and mean squared relative error (MSRE). The results of the comparison indicate that the proposed model which is HCA with LSSVM has the lowest RBIAS, MARE and MSRE compared to the other three models. This model predicts flood quantile more accurately and provides a promising alternative technique in estimation of flood quantiles in ungauged sites
format	Thesis
qualification_level	Master's degree
author	Roselan, Nur Shahidah
author_facet	Roselan, Nur Shahidah
author_sort	Roselan, Nur Shahidah
title	Flood frequency analysis at ungauged sites in Peninsular Malaysia using least square support vector machine
title_short	Flood frequency analysis at ungauged sites in Peninsular Malaysia using least square support vector machine
title_full	Flood frequency analysis at ungauged sites in Peninsular Malaysia using least square support vector machine
title_fullStr	Flood frequency analysis at ungauged sites in Peninsular Malaysia using least square support vector machine
title_full_unstemmed	Flood frequency analysis at ungauged sites in Peninsular Malaysia using least square support vector machine
title_sort	flood frequency analysis at ungauged sites in peninsular malaysia using least square support vector machine
granting_institution	Universiti Teknologi Malaysia, Faculty of Science
granting_department	Faculty of Science
publishDate	2014
_version_	1747817393737957376

Flood frequency analysis at ungauged sites in Peninsular Malaysia using least square support vector machine

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