Development of missing data prediction model for carbon monoxide

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Development of missing data prediction model for carbon monoxide

Carbon monoxide (CO) is one of the most important pollutants since it is selected for API calculation. Therefore, it is paramount to ensure that there is no missing data of CO during the analysis. There are numbers of occurrences that may contribute to the missing data problems such as inability o...

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Bibliographic Details
Main Authors:	Abd Rani, Nurul Latiffah, Azid, Azman, Abdullah Sani, Muhamad Shirwan, Samsudin, Mohd Saiful, Ku Yusof, Ku Mohd Kalkausar, Muhammad Amin, Siti Noor Syuhada, Khalit, Saiful Iskandar
Format:	Article
Language:	English English
Published:	Penerbit UTM Press 2019
Subjects:	QA Mathematics QA300 Analysis QD Chemistry
Online Access:	http://irep.iium.edu.my/70673/ http://irep.iium.edu.my/70673/1/70673_Development%20of%20missing%20data%20prediction.pdf http://irep.iium.edu.my/70673/2/70673_Development%20of%20missing%20data%20prediction_WOS.pdf

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