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Application of Mahalanobis-Taguchi system in rainfall distribution.

The rainfall time series is often nonlinear and multi-time scale because of hydrology, meteorological, and human activity. Weather stations gather information on a diverse set of parameters on order to monitor and analyses patterns of rainfall. Nevertheless, not all parameters are created equal in t...

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Main Authors: Aris, N. H., Abu, M. Y., Jamil, M. A. M., M. Zaini, S. N. A., Pinueh, N. S., W. Muhamad, W. Z. A., Ramlie, F., Harudin, N., Sari, E.
Format: Article
Language:English
Published: Universiti Malaysia Pahang 2023
Subjects:
TJ Mechanical engineering and machinery
Online Access:http://eprints.utm.my/108733/1/FRamlie2023_ApplicationofMahalanobisTaguchiSystem%20in%20Rainfall%20Distribution.pdf
http://eprints.utm.my/108733/
http://dx.doi.org/10.15282/jmmst.v7i2.9582
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spelling my.utm.1087332024-11-27T09:44:37Z http://eprints.utm.my/108733/ Application of Mahalanobis-Taguchi system in rainfall distribution. Aris, N. H. Abu, M. Y. Jamil, M. A. M. M. Zaini, S. N. A. Pinueh, N. S. W. Muhamad, W. Z. A. Ramlie, F. Harudin, N. Sari, E. TJ Mechanical engineering and machinery The rainfall time series is often nonlinear and multi-time scale because of hydrology, meteorological, and human activity. Weather stations gather information on a diverse set of parameters on order to monitor and analyses patterns of rainfall. Nevertheless, not all parameters are created equal in terms of its significance or effectiveness in carrying out classification and optimization actions. The objective is to classify rainfall occurrences by the RT method and optimize the parameter selection process by the T method using Mahalanobis-Taguchi system (MTS). The data was collected using Vantage Pro2 weather station at UMPSA Gambang campus and it consists of 16 various parameters. As a results, RT method can classify the data samples in terms of MD for the months of June, October and December by utilizing the, while simultaneously the number of parameters is reduced to only those that substantially contribute to the classification. This brings the total number of parameters decrease from 16 to 8 when compared to the T method. So, this research methods offer a simplified and effective way for analyzing rainfall patterns and optimizing the data gathering processes at weather stations. Universiti Malaysia Pahang 2023-09-30 Article PeerReviewed application/pdf en http://eprints.utm.my/108733/1/FRamlie2023_ApplicationofMahalanobisTaguchiSystem%20in%20Rainfall%20Distribution.pdf Aris, N. H. and Abu, M. Y. and Jamil, M. A. M. and M. Zaini, S. N. A. and Pinueh, N. S. and W. Muhamad, W. Z. A. and Ramlie, F. and Harudin, N. and Sari, E. (2023) Application of Mahalanobis-Taguchi system in rainfall distribution. Journal Of Modern Manufacturing Systems And Technology (JMMST), 7 (2). pp. 1-8. ISSN 2636-9575 http://dx.doi.org/10.15282/jmmst.v7i2.9582 DOI:10.15282/jmmst.v7i2.9582
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Aris, N. H.
Abu, M. Y.
Jamil, M. A. M.
M. Zaini, S. N. A.
Pinueh, N. S.
W. Muhamad, W. Z. A.
Ramlie, F.
Harudin, N.
Sari, E.
Application of Mahalanobis-Taguchi system in rainfall distribution.
description The rainfall time series is often nonlinear and multi-time scale because of hydrology, meteorological, and human activity. Weather stations gather information on a diverse set of parameters on order to monitor and analyses patterns of rainfall. Nevertheless, not all parameters are created equal in terms of its significance or effectiveness in carrying out classification and optimization actions. The objective is to classify rainfall occurrences by the RT method and optimize the parameter selection process by the T method using Mahalanobis-Taguchi system (MTS). The data was collected using Vantage Pro2 weather station at UMPSA Gambang campus and it consists of 16 various parameters. As a results, RT method can classify the data samples in terms of MD for the months of June, October and December by utilizing the, while simultaneously the number of parameters is reduced to only those that substantially contribute to the classification. This brings the total number of parameters decrease from 16 to 8 when compared to the T method. So, this research methods offer a simplified and effective way for analyzing rainfall patterns and optimizing the data gathering processes at weather stations.
format Article
author Aris, N. H.
Abu, M. Y.
Jamil, M. A. M.
M. Zaini, S. N. A.
Pinueh, N. S.
W. Muhamad, W. Z. A.
Ramlie, F.
Harudin, N.
Sari, E.
author_facet Aris, N. H.
Abu, M. Y.
Jamil, M. A. M.
M. Zaini, S. N. A.
Pinueh, N. S.
W. Muhamad, W. Z. A.
Ramlie, F.
Harudin, N.
Sari, E.
author_sort Aris, N. H.
title Application of Mahalanobis-Taguchi system in rainfall distribution.
title_short Application of Mahalanobis-Taguchi system in rainfall distribution.
title_full Application of Mahalanobis-Taguchi system in rainfall distribution.
title_fullStr Application of Mahalanobis-Taguchi system in rainfall distribution.
title_full_unstemmed Application of Mahalanobis-Taguchi system in rainfall distribution.
title_sort application of mahalanobis-taguchi system in rainfall distribution.
publisher Universiti Malaysia Pahang
publishDate 2023
url http://eprints.utm.my/108733/1/FRamlie2023_ApplicationofMahalanobisTaguchiSystem%20in%20Rainfall%20Distribution.pdf
http://eprints.utm.my/108733/
http://dx.doi.org/10.15282/jmmst.v7i2.9582
_version_ 1817841638495485952
score 13.222552

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