Abstract
Nowadays efficient methods for air quality assessment are needed in order to detect negative problems in human health. A new computational model is developed in order to evaluate toxic compounds in air of urban areas that can be harmful in sensitive people, affecting their normal activities. Using the Gamma classifier (Γ), environmental variables are assessed determining their negative impact in air quality based on their toxicity limits, the average of the frequency and the deviations of toxic tests. A fuzzy inference system uses the environmental classifications providing an air quality index, which describes the pollution levels in five stages: excellent, good, regular, bad and danger respectively.
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Carbajal Hernández, J.J., Sánchez Fernández, L.P., Manrique Ramírez, P. (2010). Environmental Pattern Recognition for Assessment of Air Quality Data with the Gamma Classifier. In: Sidorov, G., Hernández Aguirre, A., Reyes García, C.A. (eds) Advances in Artificial Intelligence. MICAI 2010. Lecture Notes in Computer Science(), vol 6437. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16761-4_38
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DOI: https://doi.org/10.1007/978-3-642-16761-4_38
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