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Artificial Neural Network for Industrial and Environmental Research via Air Quality Monitoring Network
Abstract
Industrial and environmental research will always involve the study of the cause-effect relationship between emissions and the surrounding environment. The techniques of artificial intelligence such as artificial neural network can be applied in the industrial and environmental research. Chemical facilities have high risks to originate air emission events (e.g. intensive flaring and toxic gas release). They are caused by various uncertainties like equipment failure, false operation, nature disaster, or terrorist attack. Through an air-quality monitoring network, data integration is applied to identify the possible emission source and dynamic emission profiles. In this chapter, the above-mentioned application has been illustrated. It has the capability to identify the potential emission profile and characterize spatial-temporal pollutant dispersion. It provides valuable information for accidental investigations and root cause analysis for an emission event; meanwhile, it helps evaluate the regional air quality impact caused by such an emission event.
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