Clustering rainfall pattern in Malaysia using functional data analysis
Understanding rainfall pattern is important for planning and prediction in hydrology, meteorology, water planning and agriculture. There are two important features of rainfall: the rainfall amount and the probability of rainfall occurrence. The discrete raw data of rainfall precipitation was reconst...
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| Format: | Conference or Workshop Item |
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2015
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| author | Hamdan, Muhammad Fauzee Suhaila, Jamaludin Jemain, Abdul Aziz |
| author_facet | Hamdan, Muhammad Fauzee Suhaila, Jamaludin Jemain, Abdul Aziz |
| author_sort | Hamdan, Muhammad Fauzee |
| collection | ePrints |
| description | Understanding rainfall pattern is important for planning and prediction in hydrology, meteorology, water planning and agriculture. There are two important features of rainfall: the rainfall amount and the probability of rainfall occurrence. The discrete raw data of rainfall precipitation was reconstructed into rainfall amount curves by using functional data analysis method. Hierarchical clustering method with complete-linkage method was used to search for natural similar groupings of rainfall amount curves. The functional clustering illustrated the four dominant patterns for rainfall amount curves. In additional, adaptive Neyman test showed that each clusters are significantly different with from each others. |
| first_indexed | 2024-03-05T19:44:38Z |
| format | Conference or Workshop Item |
| id | utm.eprints-59186 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T19:44:38Z |
| publishDate | 2015 |
| record_format | dspace |
| spelling | utm.eprints-591862022-04-05T05:37:07Z http://eprints.utm.my/59186/ Clustering rainfall pattern in Malaysia using functional data analysis Hamdan, Muhammad Fauzee Suhaila, Jamaludin Jemain, Abdul Aziz QA Mathematics Understanding rainfall pattern is important for planning and prediction in hydrology, meteorology, water planning and agriculture. There are two important features of rainfall: the rainfall amount and the probability of rainfall occurrence. The discrete raw data of rainfall precipitation was reconstructed into rainfall amount curves by using functional data analysis method. Hierarchical clustering method with complete-linkage method was used to search for natural similar groupings of rainfall amount curves. The functional clustering illustrated the four dominant patterns for rainfall amount curves. In additional, adaptive Neyman test showed that each clusters are significantly different with from each others. 2015 Conference or Workshop Item PeerReviewed Hamdan, Muhammad Fauzee and Suhaila, Jamaludin and Jemain, Abdul Aziz (2015) Clustering rainfall pattern in Malaysia using functional data analysis. In: 2nd ISM International Statistical Conference 2014: Empowering the Applications of Statistical and Mathematical Sciences, ISM 2014, 12 - 14 August 2014, Kuantan, Pahang. http://dx.doi.org/10.1063/1.4907466 |
| spellingShingle | QA Mathematics Hamdan, Muhammad Fauzee Suhaila, Jamaludin Jemain, Abdul Aziz Clustering rainfall pattern in Malaysia using functional data analysis |
| title | Clustering rainfall pattern in Malaysia using functional data analysis |
| title_full | Clustering rainfall pattern in Malaysia using functional data analysis |
| title_fullStr | Clustering rainfall pattern in Malaysia using functional data analysis |
| title_full_unstemmed | Clustering rainfall pattern in Malaysia using functional data analysis |
| title_short | Clustering rainfall pattern in Malaysia using functional data analysis |
| title_sort | clustering rainfall pattern in malaysia using functional data analysis |
| topic | QA Mathematics |
| work_keys_str_mv | AT hamdanmuhammadfauzee clusteringrainfallpatterninmalaysiausingfunctionaldataanalysis AT suhailajamaludin clusteringrainfallpatterninmalaysiausingfunctionaldataanalysis AT jemainabdulaziz clusteringrainfallpatterninmalaysiausingfunctionaldataanalysis |