2014
DOI: 10.5296/emsd.v3i2.6290
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Rainfall Analysis over Mauritius Using Principal Component Analysis

Abstract: Principal Component Analysis (PCA) is one of the most popular dimensionality-reduction Environmental Management and Sustainable Development ISSN 2164-7682 2014 www.macrothink.org/emsd 95 techniques used for the purpose of classification. It has gained popularity because of its ease of use and optimal nature in a mean square error sense. This paper focuses on an analysis of PCA as a classification tool for rainfall images. Rainfall maps were generated using monthly precipitation data from 226 stations over Mau… Show more

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Cited by 12 publications
(7 citation statements)
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“…This is due to the influence of the southeast trade winds (SETWs) on the climate of the island. The resulting effect is a decreasing gradient in precipitation between the southeast and northwest, also observed by Fowdur et al (2014) and Staub et al (2014). This is especially seen on the central plateau which comprises the three inland precipitation regions (regions 2, 3 and 6) determined by the CA.…”
Section: Discussionmentioning
confidence: 83%
See 3 more Smart Citations
“…This is due to the influence of the southeast trade winds (SETWs) on the climate of the island. The resulting effect is a decreasing gradient in precipitation between the southeast and northwest, also observed by Fowdur et al (2014) and Staub et al (2014). This is especially seen on the central plateau which comprises the three inland precipitation regions (regions 2, 3 and 6) determined by the CA.…”
Section: Discussionmentioning
confidence: 83%
“…The resulting effect is a decreasing gradient in precipitation between the southeast and northwest, also observed by Fowdur et al . () and Staub et al . ().…”
Section: Discussionmentioning
confidence: 85%
See 2 more Smart Citations
“…A recent work by (Fowdar et al, 2014) was done on the classification of rainfall patterns in Mauritius using principal component analysis. However the development of forecasting techniques for rainfall prediction has attracted much interest across the globe.…”
Section: Introductionmentioning
confidence: 99%