DocumentCode :
538878
Title :
Study of Coupling Receptor to Dispersion Models with a Genetic Algorithm
Author :
Zhang, Jing ; Wang, Qinghua ; Li, Can
Author_Institution :
Sch. of Economic & Manage., Beijing Univ. of Chem. & Technol., Beijing, China
Volume :
1
fYear :
2010
fDate :
16-17 Dec. 2010
Firstpage :
340
Lastpage :
344
Abstract :
The paper introduce coupling receptor to dispersion models using a genetic algorithm. The receptor model is based on the nested source apportionment technique and the dispersion model is a basic Gaussian puff model. Coupling process is continuing through the iterative with a genetic algorithm allows to minimize the residual, which obtained the optimal solution. It expatiate the feasibility of coupling the two models with a genetic algorithm. The technique described here could prove useful for apportioning monitored pollutant to its sources, calibrating dispersion models, source position identification, monitor sitting, and estimating total uncertainty. It will be helpful to reinforce safety management and prevents pollutant leakage of the chemical plant.
Keywords :
Gaussian processes; air pollution; chemical industry; genetic algorithms; Gaussian puff model; air pollution monitoring; chemical plant; coupling receptor; dispersion model; genetic algorithm; iterative algorithm; nested source apportionment technique; optimal solution; pollutant leakage; safety management; Atmospheric modeling; Biological system modeling; Calibration; Couplings; Dispersion; Monitoring; Optimization; Dispersion model; Genetic algorithm; Nested source apportionment technique; Safety management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems (GCIS), 2010 Second WRI Global Congress on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-9247-3
Type :
conf
DOI :
10.1109/GCIS.2010.104
Filename :
5708773
Link To Document :
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