Neuro-Fuzzy Analysis of Atmospheric Pollution
Fecha de publicación
Springer Science + Business Media
Hybrid Artificial Intelligent Systems. 10th International Conference, HAIS 2015, Bilbao, Spain, June 22-24, 2015, Proceedings. Lecture Notes in Computer Science. Volumen 9121, pp. 382-392.
Present study proposes the application of different soft-computing and statistical techniques to the characterization of atmospheric conditions in Spain. The main goal is to visualize and analyze the air quality in a certain region of Spain (Madrid) to better understand its circumstances and evolution. To do so, real-life data from three data acquisition stations are analysed. The main pollutants acquired by these stations are studied in order to research how the geographical location of these stations and the different seasons of the year are decisive in the behavior of air pollution. Different techniques for dimensionality reduction together with clustering techniques have been applied, in a combination of neural and fuzzy paradigms.
978-3-319-19643-5(Print) / 978-3-319-19644-2(Online)
0302-9743(Print) / 1611-3349(Online)
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