The potential of canonical correlation analysis in multivariable screening of climate model

The statistical downscaling model (SDSM) been used to analyse the potential changes of local climate trend in the long term. The difficulty of the SDSM model in selecting the best predictors group which having good association to the local climate. Even the SDSM provides screening process to analys...

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Main Authors:	Nurul Nadrah Aqilah, Tukimat, Sobri, Harun, Mohd Yuhyi, Mohd Tadza
Format:	Conference or Workshop Item
Language:	English
Published:	IOP Publishing 2019
Subjects:	TA Engineering (General). Civil engineering (General)
Online Access:	http://umpir.ump.edu.my/id/eprint/26036/ http://umpir.ump.edu.my/id/eprint/26036/ http://umpir.ump.edu.my/id/eprint/26036/1/The%20potential%20of%20canonical%20correlation.pdf

id	ump-26036
recordtype	eprints
spelling	ump-260362019-12-17T03:49:40Z http://umpir.ump.edu.my/id/eprint/26036/ The potential of canonical correlation analysis in multivariable screening of climate model Nurul Nadrah Aqilah, Tukimat Sobri, Harun Mohd Yuhyi, Mohd Tadza TA Engineering (General). Civil engineering (General) The statistical downscaling model (SDSM) been used to analyse the potential changes of local climate trend in the long term. The difficulty of the SDSM model in selecting the best predictors group which having good association to the local climate. Even the SDSM provides screening process to analyse the predictor-rainfall relationship, however it has limited ability in analyzing multiple variables from 26 predictors with 10 rainfall stations around Kedah state, Malaysia. In this regard, the Canonical Correlation Analysis (CCA) been used to analyse the multi predictor-rainfall relationships. The concept of canonical coefficient is sufficient to show the capability and reliability of the predictors based on the percentages of variance that can explained in the dependent variable using the independent variable. There were 10 predictors’ group have been developed and one predictor’s group was built based on the CCA result. The performances of these predictors groups were tested using statistical analyses. Results revealed that the predictors group selected by the CCA method has produced smaller values of MAE and MSE for all stations except at station of Ladang Tanjung Pauh. The box plot’s results, which generated from one hundred simulated samples, indicated that the performance of CCA method was remarkable. ical researchers while designing the studies to maximize the benefits of the secondary data. IOP Publishing 2019 Conference or Workshop Item PeerReviewed pdf en cc_by http://umpir.ump.edu.my/id/eprint/26036/1/The%20potential%20of%20canonical%20correlation.pdf Nurul Nadrah Aqilah, Tukimat and Sobri, Harun and Mohd Yuhyi, Mohd Tadza (2019) The potential of canonical correlation analysis in multivariable screening of climate model. In: IOP Conference Series: Earth and Environmental Science, International Conference on Agricultural Technology, Engineering and Environmental Sciences, 21-22 August 2019 , Banda Aceh, Indonesia. pp. 1-10., 365 (012025). ISSN 1755-1315 https://doi.org/10.1088/1755-1315/365/1/012025
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TA Engineering (General). Civil engineering (General)
spellingShingle	TA Engineering (General). Civil engineering (General) Nurul Nadrah Aqilah, Tukimat Sobri, Harun Mohd Yuhyi, Mohd Tadza The potential of canonical correlation analysis in multivariable screening of climate model
description	The statistical downscaling model (SDSM) been used to analyse the potential changes of local climate trend in the long term. The difficulty of the SDSM model in selecting the best predictors group which having good association to the local climate. Even the SDSM provides screening process to analyse the predictor-rainfall relationship, however it has limited ability in analyzing multiple variables from 26 predictors with 10 rainfall stations around Kedah state, Malaysia. In this regard, the Canonical Correlation Analysis (CCA) been used to analyse the multi predictor-rainfall relationships. The concept of canonical coefficient is sufficient to show the capability and reliability of the predictors based on the percentages of variance that can explained in the dependent variable using the independent variable. There were 10 predictors’ group have been developed and one predictor’s group was built based on the CCA result. The performances of these predictors groups were tested using statistical analyses. Results revealed that the predictors group selected by the CCA method has produced smaller values of MAE and MSE for all stations except at station of Ladang Tanjung Pauh. The box plot’s results, which generated from one hundred simulated samples, indicated that the performance of CCA method was remarkable. ical researchers while designing the studies to maximize the benefits of the secondary data.
format	Conference or Workshop Item
author	Nurul Nadrah Aqilah, Tukimat Sobri, Harun Mohd Yuhyi, Mohd Tadza
author_facet	Nurul Nadrah Aqilah, Tukimat Sobri, Harun Mohd Yuhyi, Mohd Tadza
author_sort	Nurul Nadrah Aqilah, Tukimat
title	The potential of canonical correlation analysis in multivariable screening of climate model
title_short	The potential of canonical correlation analysis in multivariable screening of climate model
title_full	The potential of canonical correlation analysis in multivariable screening of climate model
title_fullStr	The potential of canonical correlation analysis in multivariable screening of climate model
title_full_unstemmed	The potential of canonical correlation analysis in multivariable screening of climate model
title_sort	potential of canonical correlation analysis in multivariable screening of climate model
publisher	IOP Publishing
publishDate	2019
url	http://umpir.ump.edu.my/id/eprint/26036/ http://umpir.ump.edu.my/id/eprint/26036/ http://umpir.ump.edu.my/id/eprint/26036/1/The%20potential%20of%20canonical%20correlation.pdf
first_indexed	2023-09-18T22:40:17Z
last_indexed	2023-09-18T22:40:17Z
_version_	1777416869296209920

The potential of canonical correlation analysis in multivariable screening of climate model

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