CINECA IRIS Institutional Research Information System
IRIS è la soluzione IT che facilita la raccolta e la gestione dei dati relativi alle attività e ai prodotti della ricerca. Fornisce a ricercatori, amministratori e valutatori gli strumenti per monitorare i risultati della ricerca, aumentarne la visibilità e allocare in modo efficace le risorse disponibili.
EnglishThe 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 |
File in questo prodotto:
Pubblicazioni consigliate
Copyright © 2021