A technique of fuzzy C-Mean in multiple linear regression model toward paddy yield
. In this paper, we propose a hybrid model which is a combination of multiple linear regression model and fuzzy c-means method. This research involved a relationship between 20 variates of the top soil that are analyzed prior to planting of paddy yields at standard fertilizer rates. Data used...
| Main Authors: | , , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2018
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/7006/ http://eprints.uthm.edu.my/7006/1/P9889_718ddb01ea16506f15e4ff1dc78fd2b7.pdf |
| _version_ | 1848888974139981824 |
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| author | Wahab, Nur Syazwan Rusiman, Mohd Saifullah Mohamad, Mahathir Azmi, Nur Amira Che Him, Norziha Kamardan, M. Ghazali Ali, Maselan |
| author_facet | Wahab, Nur Syazwan Rusiman, Mohd Saifullah Mohamad, Mahathir Azmi, Nur Amira Che Him, Norziha Kamardan, M. Ghazali Ali, Maselan |
| author_sort | Wahab, Nur Syazwan |
| building | UTHM Institutional Repository |
| collection | Online Access |
| description | . In this paper, we propose a hybrid model which is a combination of multiple linear
regression model and fuzzy c-means method. This research involved a relationship between 20
variates of the top soil that are analyzed prior to planting of paddy yields at standard fertilizer
rates. Data used were from the multi-location trials for rice carried out by MARDI at major
paddy granary in Peninsular Malaysia during the period from 2009 to 2012. Missing
observations were estimated using mean estimation techniques. The data were analyzed using
multiple linear regression model and a combination of multiple linear regression model and
fuzzy c-means method. Analysis of normality and multicollinearity indicate that the data is
normally scattered without multicollinearity among independent variables. Analysis of fuzzy c�means cluster the yield of paddy into two clusters before the multiple linear regression model
can be used. The comparison between two method indicate that the hybrid of multiple linear
regression model and fuzzy c-means method outperform the multiple linear regression model
with lower value of mean square error. |
| first_indexed | 2025-11-15T20:18:48Z |
| format | Conference or Workshop Item |
| id | uthm-7006 |
| institution | Universiti Tun Hussein Onn Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T20:18:48Z |
| publishDate | 2018 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uthm-70062022-05-24T01:19:06Z http://eprints.uthm.edu.my/7006/ A technique of fuzzy C-Mean in multiple linear regression model toward paddy yield Wahab, Nur Syazwan Rusiman, Mohd Saifullah Mohamad, Mahathir Azmi, Nur Amira Che Him, Norziha Kamardan, M. Ghazali Ali, Maselan T Technology (General) . In this paper, we propose a hybrid model which is a combination of multiple linear regression model and fuzzy c-means method. This research involved a relationship between 20 variates of the top soil that are analyzed prior to planting of paddy yields at standard fertilizer rates. Data used were from the multi-location trials for rice carried out by MARDI at major paddy granary in Peninsular Malaysia during the period from 2009 to 2012. Missing observations were estimated using mean estimation techniques. The data were analyzed using multiple linear regression model and a combination of multiple linear regression model and fuzzy c-means method. Analysis of normality and multicollinearity indicate that the data is normally scattered without multicollinearity among independent variables. Analysis of fuzzy c�means cluster the yield of paddy into two clusters before the multiple linear regression model can be used. The comparison between two method indicate that the hybrid of multiple linear regression model and fuzzy c-means method outperform the multiple linear regression model with lower value of mean square error. 2018 Conference or Workshop Item PeerReviewed text en http://eprints.uthm.edu.my/7006/1/P9889_718ddb01ea16506f15e4ff1dc78fd2b7.pdf Wahab, Nur Syazwan and Rusiman, Mohd Saifullah and Mohamad, Mahathir and Azmi, Nur Amira and Che Him, Norziha and Kamardan, M. Ghazali and Ali, Maselan (2018) A technique of fuzzy C-Mean in multiple linear regression model toward paddy yield. In: ISMAP 2017, October 28, 2017, Batu Pahat, Johor. https://doi.org/10.1088/1742-6596/995/1/012010 |
| spellingShingle | T Technology (General) Wahab, Nur Syazwan Rusiman, Mohd Saifullah Mohamad, Mahathir Azmi, Nur Amira Che Him, Norziha Kamardan, M. Ghazali Ali, Maselan A technique of fuzzy C-Mean in multiple linear regression model toward paddy yield |
| title | A technique of fuzzy C-Mean in multiple linear regression
model toward paddy yield |
| title_full | A technique of fuzzy C-Mean in multiple linear regression
model toward paddy yield |
| title_fullStr | A technique of fuzzy C-Mean in multiple linear regression
model toward paddy yield |
| title_full_unstemmed | A technique of fuzzy C-Mean in multiple linear regression
model toward paddy yield |
| title_short | A technique of fuzzy C-Mean in multiple linear regression
model toward paddy yield |
| title_sort | technique of fuzzy c-mean in multiple linear regression
model toward paddy yield |
| topic | T Technology (General) |
| url | http://eprints.uthm.edu.my/7006/ http://eprints.uthm.edu.my/7006/ http://eprints.uthm.edu.my/7006/1/P9889_718ddb01ea16506f15e4ff1dc78fd2b7.pdf |