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2018 | OriginalPaper | Buchkapitel

Automatic Classification of Air Pollution and Human Health

verfasst von : Rachida El Morabet, Abderrahmane Adoui El Ouadrhiri, Jaroslav Burian, Said Jai Andaloussi, Said El Mouak, Abderrahim Sekkaki

Erschienen in: Big Data, Cloud and Applications

Verlag: Springer International Publishing

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Abstract

We are entering an era of data, which are spatially and temporally referenced, this paper offers an opportunity to enhance geographic understanding, more especially in the term of air pollution and its relationship with human health, especially in the city of Mohammedia (Northern part of Morocco). Authors build a tool in the form of data mining scheme, to couple the data with machine learning, in order to automatically align the features of massive and complex data sets for human interaction in environmental social systems. New proposed approach is based on PCA (Principle Component Analysis) and K-SVM (Kernel Support Vector Machine). The system tests result is accomplished, an accuracy of 93% in testing data taken from daily values during 3 years.

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Vorheriges Kapitel Towards for Using Spectral Clustering in Graph Mining

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Titel: Automatic Classification of Air Pollution and Human Health
verfasst von: Rachida El Morabet
Abderrahmane Adoui El Ouadrhiri
Jaroslav Burian
Said Jai Andaloussi
Said El Mouak
Abderrahim Sekkaki
Verlag: Springer International Publishing
Buch: Big Data, Cloud and Applications
Print ISBN: 978-3-319-96291-7

Electronic ISBN: 978-3-319-96292-4

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-96292-4_13

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