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A technique of fuzzy c-mean in multiple linear regression model toward paddy yield

Wahab, Nur Syazwan and Rusiman, Mohd Saifullah and Mohamad, Mahathir and Azmi, Nur Amira and Che Him, Norziha and Kamardan, M. Ghazali (2017) A technique of fuzzy c-mean in multiple linear regression model toward paddy yield. In: International Seminar on Mathematics and Physics in Sciences and Technology (ISMAP 2017), 28-29 October 2017, Batu Pahat, Johor, Malaysia.

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Abstract

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 cmeans 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.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Applied Science and Technology > Department of Mathematics and Statistic
Depositing User: Mr. Mohammad Shaifulrip Ithnin
Date Deposited: 31 Jul 2019 00:59
Last Modified: 31 Jul 2019 00:59
URI: http://eprints.uthm.edu.my/id/eprint/11384
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