Abstract
A field study was carried out in Yinchuan to gather and evaluate information about the real environment. O 3 (Ozone), PM 10 (particle 10 um in diameter and smaller) and SO 2 (sulphur monoxide) constitute the major concern for air quality of Yinchuan. This paper addresses the problem of the predictions of such three pollutants by using the ANN. Because ANNs are non-linear mapping structure based on the function of the human brain. They have been shown to be universal and highly flexible function approximation for any date. These make powerful tools for models, especially when the underlying data relationship is unknown.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Sun, Y.Q., Hui, Q., Wu, X.H.: Hydrogeochemical characteristics of groundwater depression cones in Yinchuan City. Northwest China, Chinese Journal of Geochemistry 26, 350–355 (2007)
Sun, Y.C., Miao, O.L., Li, Y.C.: Prediction result analysis of air quality dynamic prediction system in Yinchuan city. Arid Meteorology 24, 89–94 (2006)
Wang, W., Li, X.H., Wang, X.F.: Levels and chiral signatures of organochlorine pesticides in urban soils of Yinchuan. China Bull. Environ. Contam. Toxicol. 82, 505–509 (2009) (in Chinese with English abstract)
Antonic, O., Hatic, D., Krian, J., Bukocev, D.: Modelling groundwater regime acceptable for the forest survival after the building of the hydro-electric power plant. Ecol. Model. 138, 277–288 (2001)
NSCGPRC: Code for Design of Metro (GB50157-2003). China Planning, Beijing (2003)
EPA: National ambient air quality standards for particulate matter, final rule. EPA-HQ-OAR-2001-0017, FRL-8225-3, 40 CFR Part 50, Research Triangle Park, NC (October 2006)
Han, Y.W., Gao, J.X., Li, H.: Ecology suitability analysis on the industry overall arrangement plan of Ningdong Energy Sources and Chemical Industry Base. Environmental Science and Management 32, 143–147 (2007)
EPA: PM standards (2007b), http://www.epa.gov/air/particlepollution/standards.html
EPA: Final clean air fine particle implementation rule for implementation of 1997 Pm 2.5 standards: Fact sheet (2007a), http://www.epa.gov/pmdesignations/documents/Mar07/factsheet.htm
Boger, Z., Guterman, H.: Knowledge extraction from artificial neural network models. In: IEEE Systems, Man and Cybernetics Conference, Orlando, FL (1997)
Bishop, A.: Neural Networks for Pattern Recognition. Oxford University Press, Oxford (1995)
Wang, Y.M., Zhao, Y.F.: Issues of environmental protection and ecological construction of Ningdong Energy and Chemistry Industry Base. Ningxia Engineering Technology 7, 190–193 (2008) (in Chinese with English abstract)
Darken, C., Moody, J.: Note on learning rate schedulesfor stochastic optimization. In: Lippman, R.P., Moody, J.E., Touretzky, D.S. (eds.), pp. 832–838 (1991)
Giustolisi, O., Mastrorilli, M.: Realizzazione di un modello connessionista applicato a un problema di idrologia urbana. In: XXIV Conv. di Idraulica e Costruz. Idrauliche, Italy (1994)
Chu, G., Mi, W.B.: An analysis to the ecological carrying capacity of Yinchuan city. Urban Problems 10, 39–42 (2008) (in Chinese with English abstract)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Li, F. (2010). Air Quality Prediction in Yinchuan by Using Neural Networks. In: Tan, Y., Shi, Y., Tan, K.C. (eds) Advances in Swarm Intelligence. ICSI 2010. Lecture Notes in Computer Science, vol 6146. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13498-2_71
Download citation
DOI: https://doi.org/10.1007/978-3-642-13498-2_71
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13497-5
Online ISBN: 978-3-642-13498-2
eBook Packages: Computer ScienceComputer Science (R0)