Chuan, Zun Liang and Sayang, Mohd Deni and Fam, Soo-Fen and Noriszura, Ismail (2020) The effectiveness of a probabilistic principal component analysis model and expectation maximisation algorithm in treating missing daily rainfall data. Asia-Pacific Journal of Atmospheric Sciences, 56 (1). pp. 119-129. ISSN 1976-7633. (Published)
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Abstract
The reliability and accuracy of a risk assessment of extreme hydro-meteorological events are highly dependent on the quality of the historical rainfall time series data. However, missing data in a time series such as this could result in lower quality data. Therefore, this paper proposes a multiple-imputation algorithm for treating missing data without requiring information from adjoining monitoring stations. The proposed imputation algorithms are based on the M-component probabilistic principal component analysis model and an expectation maximisation algorithm (MPPCA-EM). In order to evaluate the effectiveness of the MPPCA-EM imputation algorithm, six distinct historical daily rainfall time series data were recorded from six monitoring stations. These stations were located at the coastal and inland regions of the East-Coast Economic Region (ECER) Malaysia. The results of analysis show that, when it comes to treating missing historical daily rainfall time series data recorded from coastal monitoring stations, the 2-component probabilistic principal component analysis model and expectation-maximisation algorithm (2PPCA-EM) were found to be superior to the single- and multiple-imputation algorithms proposed in previous studies. On the contrary, the single-imputation algorithms as proposed in previous studies were superior to the MPPCA-EM imputation algorithms when treating missing historical daily rainfall time series data recorded from inland monitoring stations.
| Item Type: | Article |
|---|---|
| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | Expectation maximization algorithms; Missing daily rainfall; Probabilistic principal component analysis model; VIKOR technique |
| Subjects: | G Geography. Anthropology. Recreation > GE Environmental Sciences |
| Faculty/Division: | Faculty of Industrial Sciences And Technology Center for Mathematical Science |
| Depositing User: | Dr. Zun Liang Chuan |
| Date Deposited: | 14 Oct 2021 04:37 |
| Last Modified: | 17 Jan 2022 04:40 |
| URI: | http://umpir.ump.edu.my/id/eprint/30291 |
| Download Statistic: | View Download Statistics |
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