The level of nitrogen oxides in atmosphere has been increasing in the last century, mainly due to human activities. Unfortunately nitrogen oxides have a number of negative effects on air quality: they contribute to photochemical smog, visibility reduction, acid rain and also have a negative impact on human health. In the paper a novel strategy to improve the estimation of nitrogen oxides emissions produced by chimneys of refineries is proposed. In particular nonlinear models, obtained by using MLPs neural networks, which are being a commonly used tool in processing data acquired in petrochemical processes, are proposed. The performance of the proposed model with respect to both traditional heuristic models and linear models are described
Titolo: | Improving Monitoring of NOx Emissions in Refineries |
Autori: | |
Data di pubblicazione: | 2004 |
Abstract: | The level of nitrogen oxides in atmosphere has been increasing in the last century, mainly due to human activities. Unfortunately nitrogen oxides have a number of negative effects on air quality: they contribute to photochemical smog, visibility reduction, acid rain and also have a negative impact on human health. In the paper a novel strategy to improve the estimation of nitrogen oxides emissions produced by chimneys of refineries is proposed. In particular nonlinear models, obtained by using MLPs neural networks, which are being a commonly used tool in processing data acquired in petrochemical processes, are proposed. The performance of the proposed model with respect to both traditional heuristic models and linear models are described |
Handle: | http://hdl.handle.net/11570/1906398 |
ISBN: | 9780780382480 |
Appare nelle tipologie: | 14.d.3 Contributi in extenso in Atti di convegno |