The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments

The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments

Due to the limited of historical precipitation records, agglomerative hierarchical clustering algorithms widely used to extrapolate information from gauged to ungauged precipitation catchments in yielding a more reliable projection of extreme hydro-meteorological events such as extreme precipitation...

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Main Authors: Chuan, Zun Liang, Wan Nur Syahidah, Wan Yusoff, Azlyna, Senawi, Noriszura, Ismail, Ling, Wendy Shinyie, Tan, Lit Ken, Fam, Soo-Fen
Format: Conference or Workshop Item
Language:English
Published: Institute of Physics Publishing 2018
Subjects:
QA Mathematics
Online Access:http://umpir.ump.edu.my/id/eprint/20975/
http://umpir.ump.edu.my/id/eprint/20975/
http://umpir.ump.edu.my/id/eprint/20975/1/MSEM3421070.pdf
id ump-20975
recordtype eprints
spelling ump-209752018-06-11T07:51:00Z http://umpir.ump.edu.my/id/eprint/20975/ The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments Chuan, Zun Liang Wan Nur Syahidah, Wan Yusoff Azlyna, Senawi Noriszura, Ismail Ling, Wendy Shinyie Tan, Lit Ken Fam, Soo-Fen QA Mathematics Due to the limited of historical precipitation records, agglomerative hierarchical clustering algorithms widely used to extrapolate information from gauged to ungauged precipitation catchments in yielding a more reliable projection of extreme hydro-meteorological events such as extreme precipitation events. However, identifying the optimum number of homogeneous precipitation catchments accurately based on the dendrogram resulted using agglomerative hierarchical algorithms are very subjective. The main objective of this study is to propose an efficient regionalized algorithm to identify the homogeneous precipitation catchments for non-stationary precipitation time series. The homogeneous precipitation catchments are identified using average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling, while uncentered correlation coefficient as the similarity measure. The regionalized homogeneous precipitation is consolidated using K-sample Anderson Darling non-parametric test. The analysis result shows the proposed regionalized algorithm performed more better compared to the proposed agglomerative hierarchical clustering algorithm in previous studies. Institute of Physics Publishing 2018-04-06 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/20975/1/MSEM3421070.pdf Chuan, Zun Liang and Wan Nur Syahidah, Wan Yusoff and Azlyna, Senawi and Noriszura, Ismail and Ling, Wendy Shinyie and Tan, Lit Ken and Fam, Soo-Fen (2018) The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments. In: IOP Conference Series: Materials Science and Engineering: International Conference on Innovative Technology, Engineering and Sciences 2018, iCITES 2018, 1-2 March 2018 , Pekan Campus Library Pekan, Pahang. pp. 1-10., 342 (1). ISBN 17578981 http://iopscience.iop.org/article/10.1088/1757-899X/342/1/012070
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic QA Mathematics
spellingShingle QA Mathematics
Chuan, Zun Liang
Wan Nur Syahidah, Wan Yusoff
Azlyna, Senawi
Noriszura, Ismail
Ling, Wendy Shinyie
Tan, Lit Ken
Fam, Soo-Fen
The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments
description Due to the limited of historical precipitation records, agglomerative hierarchical clustering algorithms widely used to extrapolate information from gauged to ungauged precipitation catchments in yielding a more reliable projection of extreme hydro-meteorological events such as extreme precipitation events. However, identifying the optimum number of homogeneous precipitation catchments accurately based on the dendrogram resulted using agglomerative hierarchical algorithms are very subjective. The main objective of this study is to propose an efficient regionalized algorithm to identify the homogeneous precipitation catchments for non-stationary precipitation time series. The homogeneous precipitation catchments are identified using average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling, while uncentered correlation coefficient as the similarity measure. The regionalized homogeneous precipitation is consolidated using K-sample Anderson Darling non-parametric test. The analysis result shows the proposed regionalized algorithm performed more better compared to the proposed agglomerative hierarchical clustering algorithm in previous studies.
format Conference or Workshop Item
author Chuan, Zun Liang
Wan Nur Syahidah, Wan Yusoff
Azlyna, Senawi
Noriszura, Ismail
Ling, Wendy Shinyie
Tan, Lit Ken
Fam, Soo-Fen
author_facet Chuan, Zun Liang
Wan Nur Syahidah, Wan Yusoff
Azlyna, Senawi
Noriszura, Ismail
Ling, Wendy Shinyie
Tan, Lit Ken
Fam, Soo-Fen
author_sort Chuan, Zun Liang
title The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments
title_short The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments
title_full The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments
title_fullStr The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments
title_full_unstemmed The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments
title_sort efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments
publisher Institute of Physics Publishing
publishDate 2018
url http://umpir.ump.edu.my/id/eprint/20975/
http://umpir.ump.edu.my/id/eprint/20975/
http://umpir.ump.edu.my/id/eprint/20975/1/MSEM3421070.pdf
first_indexed 2023-09-18T22:30:35Z
last_indexed 2023-09-18T22:30:35Z
_version_ 1777416258418900992

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