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...
| Main Authors: | , , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
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Institute of Physics Publishing
2018
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/20975/ http://umpir.ump.edu.my/id/eprint/20975/1/MSEM3421070.pdf |
| _version_ | 1848821243532279808 |
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| 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 |
| building | UMP Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T02:22:15Z |
| format | Conference or Workshop Item |
| id | ump-20975 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T02:22:15Z |
| publishDate | 2018 |
| publisher | Institute of Physics Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-209752022-01-17T04:44:27Z 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 (Published) http://iopscience.iop.org/article/10.1088/1757-899X/342/1/012070 |
| 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 |
| title | The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments
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| title_full | The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments
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| 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
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| title_short | The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments
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| title_sort | efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments |
| topic | QA Mathematics |
| 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 |