Analysis of a Neuro-Fuzzy Approach of Air Pollution: Building a Case Study
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This work illustrates the necessity of an Artificial Intelligence (AI)-based approach of air quality in urban and industrial areas. Some related results of Artificial Neural Networks (ANNs) and Fuzzy Logic (FL) for environmental data are considered: ANNs are proposed to the problem of short-term predicting of air pollutant concentrations in urban/industrial areas, with a special focus in the south-eastern Romania. The problems of designing a database about air quality in an urban/industrial area are discussed. First results confirm ANNs as an improvement of classical models and show the utility of ANNs in a well built air monitoring center.
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