Comparing rainfall patterns between regions in Peninsular Malaysia via a functional data analysis technique

2011 ◽  
Vol 411 (3-4) ◽  
pp. 197-206 ◽  
Author(s):  
Jamaludin Suhaila ◽  
Abdul Aziz Jemain ◽  
Muhammad Fauzee Hamdan ◽  
Wan Zawiah Wan Zin
2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
M. I. Adham ◽  
S. M. Shirazi ◽  
F. Othman ◽  
S. Rahman ◽  
Z. Yusop ◽  
...  

Runoff potentiality of a watershed was assessed based on identifying curve number (CN), soil conservation service (SCS), and functional data analysis (FDA) techniques. Daily discrete rainfall data were collected from weather stations in the study area and analyzed through lowess method for smoothing curve. As runoff data represents a periodic pattern in each watershed, Fourier series was introduced to fit the smooth curve of eight watersheds. Seven terms of Fourier series were introduced for the watersheds 5 and 8, while 8 terms of Fourier series were used for the rest of the watersheds for the best fit of data. Bootstrapping smooth curve analysis reveals that watersheds 1, 2, 3, 6, 7, and 8 are with monthly mean runoffs of 29, 24, 22, 23, 26, and 27 mm, respectively, and these watersheds would likely contribute to surface runoff in the study area. The purpose of this study was to transform runoff data into a smooth curve for representing the surface runoff pattern and mean runoff of each watershed through statistical method. This study provides information of runoff potentiality of each watershed and also provides input data for hydrological modeling.


2015 ◽  
Vol 74 (1) ◽  
Author(s):  
W. I. Wan Norliyana ◽  
Jamaludin Suhaila

The pattern of wind and rainfall throughout Peninsular Malaysia are varied from one region to another, because of strong influences from the monsoons. In order to capture the wind and rainfall variations, a functional data analysis is introduced. The purpose of this study is to convert the wind and rainfall data into a smooth curve by using functional data analysis method. Fourier basis is used in this study since the wind and rainfall data indicated periodic pattern. In order to avoid such overfitting data, roughness penalty is added to the least square when constructing functional data object from the observed data. Result indicated that if we use a small number of bases functions, the difference is very small between with and without roughness penalty, showing that it is safer to smooth only when required. However, when a large basis function is employed, the roughness penalty should be added in order to obtain optimal fit data. Based on the contour plot of correlation and cross-correlation functions of wind and rainfall data, the relationship between both climate functions could be determined.  


2018 ◽  
Vol 2 (5) ◽  
pp. 820
Author(s):  
Raja Revolin Ismail

This research is a school action research that aims to improve teacher achievement through academicsupervision. This research was conducted at SD Negeri 009 Teluk Pauh, Cirenti District. The subjects of thisstudy were teachers of SD Negeri 009 Teluk Pauh, Cirenti Subdistrict with a total number of 12 people,consisting of 4 men and 8 women. This research was carried out in two cycles carried out based on the stages ofplanning, implementation and reflection. The data used is physical data. The average data analysis technique isdescriptive method. The results showed that teacher achievement motivation in the first cycle was 60.1% withgood categories and the cycle increased to 81.6% with very good categories.


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