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Title:
A hybrid intelligent system for the analysis of atmospheric pollution: a case study in two European regions.
A hybrid intelligent system for the analysis of atmospheric pollution: a case study in two European regions.
Authors:
Arroyo Puente, Ángel; Herrero Cosío, Álvaro; Corchado Rodríguez, Emilio; Tricio, Verónica
Journal:
Logic Journal of the IGPL. Volume 25 (6), pp. 915-937. Oxford University Press.
Publication date:
1 December 2017
ISSN:
1367-0751 (Print), 1368-9894 (Online)
The combined application of several soft-computing and statistical techniques is proposed for the characterization of atmospheric conditions in two European regions: Madrid (Spain) and Prague (Czech Republic). The resulting Hybrid Artificial Intelligence System (HAIS) combines projection models for dimensionality reduction and clustering, combining neural and fuzzy paradigms, in a decision support tool. In present article, this proposed HAIS is applied to analyse the air quality in these two geographical regions and get a better understanding of its circumstances and evolution. To do so, real-life data from six data-acquisition stations are analysed. The main pollutants recorded at these stations between 2007 and 2014, their geographical locations and seasonal changes are all studied, in a research that shows how such factors determine variations in air-borne pollutants. Furthermore, neural projections of the clustering results from data on atmospheric pollution are studied.