Ensemble of neural predictors for forecasting the atmospheric pollution

Proceedings of the International Joint Conference on Neural Networks

Volumn , Issue , 2008, Pages 643-648

  Siwek, K ^a   Osowski, S ^a   Garanty, K ^a   Sowinski M ^b  

^a WARSAW UNIVERSITY OF TECHNOLOGY   (Poland)

^b SOLTAN INSTITUTE FOR NUCLEAR STUDIES   (Poland)

Author keywords

[No Author keywords available]

Indexed keywords

AIR POLLUTION; BLIND SOURCE SEPARATION; FORECASTING; POLLUTION; SUPPORT VECTOR MACHINES;

ATMOSPHERIC POLLUTIONS; INTEGRATION TOOLS; NEURAL PREDICTORS; SUPPORT VECTORS;

NEURAL NETWORKS;

EID: 56349120672     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2008.4633862     Document Type: Conference Paper

References (13)

1. A. Cichocki, S. I. Amari, Adaptive blind signal and image processing, Wiley, 2003
2. A. Cichocki, S. Amari, K. Siwek, T. Tanaka et al., ICALAB, www.bsp.brain.riken.jp/ICALAB.
3. G. Corani, Air quality prediction in Milan: feed-forward neural networks, pruned neural networks and lazy learning, Ecological Modelling, vol. 185, 2006, pp. 513-529
4. G. Grivas, A. Chaloulakou, Artificial neural network models for predictions of PMlO hourly concentrations in greater area of Athens, Atmospheric Environment, 2006, vol, 40, pp. 1216-1229
5. S. Haykin, Neural networks, comprehensive foundation, Prentice Hall, New Jersey, 1999
6. 10 concentrations in Belgium, Atmospheric Environment, 39/18, 2005, pp. 3279-3289
7. 10 concentrations, compared with a deterministic modeling system and measurements in central Helsinki, Atmospheric Environment, 2003, vol. 37, pp. 4539-4550
8. M. Peace, K. Dirks, G. Austin, The prediction of air pollution using a site optimised model and mesoscale model wind forecast, World Weather Research Program Symposium on Nowcasting and Very Short Range Forecasting, Toulouse, 2005.
9. 10 forecasting, Atmospheric Environment, 2006, vol. 40, pp. 2845-2851
10. S. Osowski, K. Garanty, Forecasting of the daily meteorological pollution using wavelets and Support Vector Machine, Engineering Applications of Artificial Intelligence, vol. 20, No 6, 2007, pp. 745-755
11. B. Scholkopf, A. Smola, Learning with Kernels, Cambridge, MA: MIT Press, 2002
12. P. N. Tan, M. Steinbach, V. Kumar, Introduction to data mining, Pearson, 2007
13. ARMAAG Foundation Website - www.armaag.gda.pl