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Prediction of rainfall trends using Mahalanobis-Taguchi system

Full comprehension of precipitation patterns is crucially needed, especially in Pekan, a district in Pahang, Malaysia. The area is renowned for its elevated levels of precipitation, making it imperative to precisely categorize and enhance the analysis of rainfall patterns to facilitate effective res...

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Main Authors: Muhammad Arieffuddin, Mohd Jamil, Mohd Yazid, Abu, Sri Nur Areena, Mohd Zaini, Nurul Haziyani, Aris, Nur Syafikah, Pinueh, Nur Najmiyah, Jaafar, Wan Zuki Azman, Wan Muhammad, Faizir, Ramlie, Nolia, Harudin, Emelia Sari, ., Nadiatul Adilah, Ahmad Abdul Ghani
Format: Article
Language:English
Published: IRCS - ITB 2024
Subjects:
T Technology (General)
TA Engineering (General). Civil engineering (General)
Online Access:http://umpir.ump.edu.my/id/eprint/41498/1/publication7-PGRS230320.pdf
http://umpir.ump.edu.my/id/eprint/41498/
https://doi.org/10.5614/j.eng.technol.sci.2024.56.2.9
https://doi.org/10.5614/j.eng.technol.sci.2024.56.2.9
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spelling my.ump.umpir.414982024-06-10T01:48:32Z http://umpir.ump.edu.my/id/eprint/41498/ Prediction of rainfall trends using Mahalanobis-Taguchi system Muhammad Arieffuddin, Mohd Jamil Mohd Yazid, Abu Sri Nur Areena, Mohd Zaini Nurul Haziyani, Aris Nur Syafikah, Pinueh Nur Najmiyah, Jaafar Wan Zuki Azman, Wan Muhammad Faizir, Ramlie Nolia, Harudin Emelia Sari, . Nadiatul Adilah, Ahmad Abdul Ghani T Technology (General) TA Engineering (General). Civil engineering (General) Full comprehension of precipitation patterns is crucially needed, especially in Pekan, a district in Pahang, Malaysia. The area is renowned for its elevated levels of precipitation, making it imperative to precisely categorize and enhance the analysis of rainfall patterns to facilitate effective resource allocation, agricultural productivity, and catastrophe readiness. The variability of rainfall patterns is contingent upon geographical location, necessitating the collection of a comprehensive data set that includes several characteristics that influence precipitation to make reliable predictions. Data were collected from the Vantage Pro2 weather station, which is located on the UMP Pekan campus. This study used the RT method to classify rainfall and T-Method 1 to determine the degree of contribution of each parameter. Significant parameters were validated using a data set from the same type of weather station but in a different district. The results showed that the Mahalanobis-Taguchi Bee Algorithm (MTBA) is more effective than the Mahalanobis-Taguchi System (MTS) in finding the significant parameters, but the parameters were a subset of MTS Teshima. Finally, the validation with T mean-based error (Tmbe) using Mean Absolute Error (MAE) revealed a pattern of errors to provide insight to find the significant parameters of MTS. IRCS - ITB 2024-04-30 Article PeerReviewed pdf en cc_by_nc_nd_4 http://umpir.ump.edu.my/id/eprint/41498/1/publication7-PGRS230320.pdf Muhammad Arieffuddin, Mohd Jamil and Mohd Yazid, Abu and Sri Nur Areena, Mohd Zaini and Nurul Haziyani, Aris and Nur Syafikah, Pinueh and Nur Najmiyah, Jaafar and Wan Zuki Azman, Wan Muhammad and Faizir, Ramlie and Nolia, Harudin and Emelia Sari, . and Nadiatul Adilah, Ahmad Abdul Ghani (2024) Prediction of rainfall trends using Mahalanobis-Taguchi system. Journal of Engineering and Technological Sciences, 56 (2). pp. 287-303. ISSN 2337-5779. (Published) https://doi.org/10.5614/j.eng.technol.sci.2024.56.2.9 https://doi.org/10.5614/j.eng.technol.sci.2024.56.2.9
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic T Technology (General)
TA Engineering (General). Civil engineering (General)
spellingShingle T Technology (General)
TA Engineering (General). Civil engineering (General)
Muhammad Arieffuddin, Mohd Jamil
Mohd Yazid, Abu
Sri Nur Areena, Mohd Zaini
Nurul Haziyani, Aris
Nur Syafikah, Pinueh
Nur Najmiyah, Jaafar
Wan Zuki Azman, Wan Muhammad
Faizir, Ramlie
Nolia, Harudin
Emelia Sari, .
Nadiatul Adilah, Ahmad Abdul Ghani
Prediction of rainfall trends using Mahalanobis-Taguchi system
description Full comprehension of precipitation patterns is crucially needed, especially in Pekan, a district in Pahang, Malaysia. The area is renowned for its elevated levels of precipitation, making it imperative to precisely categorize and enhance the analysis of rainfall patterns to facilitate effective resource allocation, agricultural productivity, and catastrophe readiness. The variability of rainfall patterns is contingent upon geographical location, necessitating the collection of a comprehensive data set that includes several characteristics that influence precipitation to make reliable predictions. Data were collected from the Vantage Pro2 weather station, which is located on the UMP Pekan campus. This study used the RT method to classify rainfall and T-Method 1 to determine the degree of contribution of each parameter. Significant parameters were validated using a data set from the same type of weather station but in a different district. The results showed that the Mahalanobis-Taguchi Bee Algorithm (MTBA) is more effective than the Mahalanobis-Taguchi System (MTS) in finding the significant parameters, but the parameters were a subset of MTS Teshima. Finally, the validation with T mean-based error (Tmbe) using Mean Absolute Error (MAE) revealed a pattern of errors to provide insight to find the significant parameters of MTS.
format Article
author Muhammad Arieffuddin, Mohd Jamil
Mohd Yazid, Abu
Sri Nur Areena, Mohd Zaini
Nurul Haziyani, Aris
Nur Syafikah, Pinueh
Nur Najmiyah, Jaafar
Wan Zuki Azman, Wan Muhammad
Faizir, Ramlie
Nolia, Harudin
Emelia Sari, .
Nadiatul Adilah, Ahmad Abdul Ghani
author_facet Muhammad Arieffuddin, Mohd Jamil
Mohd Yazid, Abu
Sri Nur Areena, Mohd Zaini
Nurul Haziyani, Aris
Nur Syafikah, Pinueh
Nur Najmiyah, Jaafar
Wan Zuki Azman, Wan Muhammad
Faizir, Ramlie
Nolia, Harudin
Emelia Sari, .
Nadiatul Adilah, Ahmad Abdul Ghani
author_sort Muhammad Arieffuddin, Mohd Jamil
title Prediction of rainfall trends using Mahalanobis-Taguchi system
title_short Prediction of rainfall trends using Mahalanobis-Taguchi system
title_full Prediction of rainfall trends using Mahalanobis-Taguchi system
title_fullStr Prediction of rainfall trends using Mahalanobis-Taguchi system
title_full_unstemmed Prediction of rainfall trends using Mahalanobis-Taguchi system
title_sort prediction of rainfall trends using mahalanobis-taguchi system
publisher IRCS - ITB
publishDate 2024
url http://umpir.ump.edu.my/id/eprint/41498/1/publication7-PGRS230320.pdf
http://umpir.ump.edu.my/id/eprint/41498/
https://doi.org/10.5614/j.eng.technol.sci.2024.56.2.9
https://doi.org/10.5614/j.eng.technol.sci.2024.56.2.9
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score 13.2353115

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