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Chemometric treatment of missing elements in air quality data sets

100%

Smolinski A., Hlawiczka S.

Polish Journal of Environmental Studies

2007

tom 16

nr 4

613-622

The article reports the results of an exploratory analysis of an air monitoring data set, collected at a monitoring station in the biggest, most congested and most polluted city of the silesian region, Katowice. In order to extract important information on air pollution in this city, the strategy of exploring the data set with missing elements and outliers simultaneously existing in the data was used. The strategy assumed the initial estimation of missing elements based on the application of robust Partial Least Squares (rPLS) and outliers identification based on the so-called robust distance. After outliers identification and replacing them with missing elements, the Expectation-Maximization iterative approach (built into Principal Component Analysis (PCA)) was used for the construction of the final model.

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Providing high-quality measurement data in analytical system of air pollution monitoring and their key importance for smart cities residents

80%

Czechowski P. O., Badyda A. J., Majewski G., Oniszczuk-Jastrzabek A., Kraszewski A. K., Rogula-Kozlowska W., Owczarek T.

Annals of Warsaw University of Life Sciences - SGGW. Land Reclamation

2017

tom 49

nr 4

Ograniczanie wyników

1 Annals of Warsaw University of Life Sciences - SGGW. Land Reclamation

1 Polish Journal of Environmental Studies

1 Badyda A. J.

1 Czechowski P. O.

1 Hlawiczka S.

1 Kraszewski A. K.

1 Majewski G.

1 Oniszczuk-Jastrzabek A.

1 Owczarek T.

1 Rogula-Kozlowska W.

1 Smolinski A.

1 2017

1 2007

Wyniki wyszukiwania

Chemometric treatment of missing elements in air quality data sets

Providing high-quality measurement data in analytical system of air pollution monitoring and their key importance for smart cities residents