Multivariate Statistical Modeling On Industrial Dust Emissions From Quarries
In this research, multivariate statistical techniques such as principal component analysis (PCA), reliability analysis (RA) and multivariate regression analysis (MRA) were applied for the development of new quarry dust model. These statistical techniques were employed to evaluate the variations and...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2012
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| Subjects: | |
| Online Access: | http://eprints.usm.my/60874/1/Pages%20from%20Izhar.pdf http://eprints.usm.my/60874/ |
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| Summary: | In this research, multivariate statistical techniques such as principal component analysis (PCA), reliability analysis (RA) and multivariate regression analysis (MRA)
were applied for the development of new quarry dust model. These statistical techniques were employed to evaluate the variations and interpretation of large complex air quality data set of dust deposition surrounding quarry area, generated during 10 years (2000-2010) monitoring of 15 variables at 18 different quarry sites in Malaysia (5,610 observations). |
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