Abstract
The main goal of this work is to supply the directives for the design of an environmental monitoring system able to estimate and predict the pollutant values of Villa San Giovanni, an important townon the Messina channel (Italy). For this purpose, neuro-fuzzy inference techniques are exploited. In particular, by using a MatLab® Toolbox, sophisticated Fuzzy Inferece Systems (FISs) were carried out. The inference engine is a bank of fuzzy rules. Each nxle is of the IF… THEN structure in terms of linguistic frameworks in which the easy understanding due to the open box structure can help the politicians to take decisions about the urban traffic. In addition, a comparisons with “black box” techniques as Neural Networks (NN) are taken into account.
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© 2002 Springer-Verlag London Limited
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Versaci, M. (2002). Neuro-Fuzzy Techniques to Estimate and Predict Atmospheric Pollutant Levels. In: Tagliaferri, R., Marinaro, M. (eds) Neural Nets WIRN Vietri-01. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-0219-9_30
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DOI: https://doi.org/10.1007/978-1-4471-0219-9_30
Publisher Name: Springer, London
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