NN-AirPol: A neural-networks-based method for air pollution evaluation and control

International Journal of Environment and Pollution

Volumn 28, Issue 3-4, 2006, Pages 310-325

  Karaca, Ferhat ^a   Nikov, Alexander ^a   Alagha, Omar ^a  

^a FATIH UNIVERSITY   (Turkey)

Author keywords

Air pollution; Backpropagation algorithm; Modelling; Optimisation

Indexed keywords

ALGORITHMS; BACKPROPAGATION; FORECASTING; MATHEMATICAL MODELS; NEURAL NETWORKS;

AIR POLLUTION DATA; BACKPROPAGATION TRAINING; POLLUTION EVALUATION;

AIR POLLUTION CONTROL;

SULFUR DIOXIDE;

ARTIFICIAL NEURAL NETWORK; ATMOSPHERIC MODELING; ATMOSPHERIC POLLUTION; BACK PROPAGATION; PARTICULATE MATTER; PERFORMANCE ASSESSMENT; POLLUTION CONTROL; POLLUTION MONITORING; SULFUR DIOXIDE; WEATHER FORECASTING;

AIR POLLUTION; AIR POLLUTION CONTROL; ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOENGINEERING; ENVIRONMENTAL FACTOR; FORECASTING; METEOROLOGY; PARTICULATE MATTER; PUBLICATION;

EURASIA; ISTANBUL [TURKEY]; TURKEY;

EID: 33845414100     PISSN: 09574352     EISSN: None     Source Type: Journal    
DOI: 10.1504/IJEP.2006.011214     Document Type: Article

References (39)

1. Abdi, H., Valentin, D., Edelman, B. and O'Toole, A.J. (1996) 'A widrow-hoff learning rule for a generalization of the linear auto-associator', Journal of Mathematical Psychology, Vol. 40, No. 2, pp. 175-182.
2. Asha, B., Chelani, C.V., Chalapati Rao, K., Phadke, M. and Kasan, M.Z. (2002) 'Prediction of sulphur dioxide concentration using artificial neural networks', Environmental Modelling and Software, Vol. 17, No. 2, pp.159-166.
3. 2 concentrations in highly polluted industrial areas of complex terrain', Atmospheric Environment, Vol. 27, No. 2, pp.221-230.
4. Chau, K.W. (2004a) 'River stage forecasting with particle swarm optimization', Lecture Notes in Computer Science, Vol. 3029, pp.1166-1173.
5. Chau, K.W. (2004b) 'Rainfall-runoff correlation with particle swarm optimization algorithm', Lecture Notes in Computer Science, Vol. 3174, pp.970-975.
6. Chau, K.W. (2005) 'A split-step PSO algorithm in prediction of water quality pollution', Lecture Notes in Computer Science, Vol. 3498, pp. 1034-1039.
7. Cheng, C.T., Chau, K.W., Sun, Y.G. and Lin, J.Y. (2005) 'Long-term prediction of discharges in Manwan Reservoir using artificial neural network models', Lecture Notes in Computer Science, Vol. 3498, pp. 1040-1045.
8. Comrie, A.C. and Diem, J.E. (1999) 'Climatology and forecast modeling of ambient carbon monoxide in Phoenix, Arizona', Atmospheric Environment, Vol. 33, pp.5023-5036.
9. Davis, J.M. and Speckman, P. (1999) 'A model for predicting maximum and 8 h average ozone in Houston', Atmospheric Environment, Vol. 33, pp.2487-2500.
10. Erman, T. (1997) 'Squatter (gecekondu) housing versus apartment housing: Turkish rural-to-urban migrant residents' perspectives', Habitat International, Vol. 21, No. 1, pp.91-106.
11. Gardner, M.W. and Dorling, S.R. (1998) 'Artificial neural networks (the multilayer perceptron) - a review of applications in the atmospheric sciences', Atmospheric Environment, Vol. 32, Nos. 14-15, pp.2627-2636.
12. x and NO2 concentrations in urban air in London', Atmospheric Environment, Vol. 33, No. 5, pp.709-719.
13. Hagan, M.T., Demuth, H.B. and Beale, M.H. (1996) Neural Network Design, PWS Publishing, Boston, MA.
14. HKKY (1986) Regulations of Air Pollution Control, Web page of Republic of Turkey Ministry of Environment and Forestry, http://www.cevreorman.gov.tr/cy/ hava.htm.
15. Jakeman, A.J., Taylor, J.A. and Simpson, R.W. (1986) 'Modeling distributions of air pollutant concentrations - II. Estimation of one and two parameter statistical distributions', Atmospheric Environment, Vol. 20, No. 12, pp.2435-2447.
16. Jorquera, H., Ricardo, P., Cipriano, A., Espejo, A.S., Letelier, M.V. and Gonzala, A. (1998) 'Forecasting ozone daily maximum levels at Santiago, Chile', Atmospheric Environment, Vol. 32, No. 20, pp.3415-3424.
17. Karaca, F., Alagha, O. and Erturk, F. (2005) 'Application of inductive learning: air pollution forecast in Istanbul City', Autosoft- Intelligent Automation and Soft Computing, Vol. 11, No. 4, pp.207-216.
18. Karaca, M., Tayanç, M. and Toros, H. (1995) 'Effects of urbanization on climate of Istanbul and Ankara', Atmospheric Environment, Vol. 29, pp.3411-3421.
19. Kolehmainen, M., Martikainen, H. and Ruuskanen, J. (2001) 'Neural networks and periodic components used in air quality forecasting', Atmospheric Environment, Vol. 35, pp.815-825.
20. 10 concentrations, compared with a deterministic modelling system and measurements in central Helsinki', Atmospheric Environment, Vol. 37, No. 32, pp.4539-4550.
21. Lu, W.Z, Fan, H. Y, Leung, A.Y.T. and Wang, J.C.K. (2002) 'Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization', Environmental Monitoring and Assessment, Vol. 79, No. 3, pp.217-230.
22. Lu, W.Z., Fan, H.Y. and Lo, S.M. (2003) 'Application of evolutionary neural network method in predicting pollutant levels in downtown area of Hong Kong', Neurocomputing, Vol. 51, pp.387-400.
23. Lu, W.Z., Wang, W.J., Wang, X.K., Yan S.H. and Lama, J.C. (2004) 'Potential assessment of a neural network model with PCA/RBF approach for forecasting pollutant trends in Mong Kok urban air, Hong Kong', Environmental Research, Vol. 96, pp.79-87.
24. Makowski, M. (2000) 'Modeling paradigms applied to the analysis of European air quality', European Journal of Operational Research, Vol. 122, pp.219-241.
25. Nguyen, D. and Widrow, B. (1990) 'Improving the learning speed of 2-layer neural networks by choosing initial values of the adaptive weights', Proceedings of the International Joint Conference on Neural Networks, Vol. 3, pp.21-26.
26. Nunnari, G., Nucifora, A.F.M. and Randieri, C. (1998) 'The application of neural techniques to the modelling of time-series of atmospheric pollution data', Ecological Modelling, Vol. 111, pp.187-205.
27. 10 concentrations 30 h in advance in Santiago, Chile', Atmospheric Environment, Vol. 36, pp.4555-4561.
28. Peton, N., Dray, G., Pearson, D., Mesbah, M. and Vuillot, B. (2000) 'Modelling and analysis of ozone episodes', Environmental Modelling and Software, Vol. 15, pp.647-652.
29. Slini, Th. and Karatzas, K. (2002) 'Statistical analysis of environmental data as the basis of forecasting: an air quality application', The Science of the Total Environment, Vol. 288, pp.227-237.
30. Spellman, G. (1999) 'An application of artificial neural networks to the prediction of surface ozone concentrations in the United Kingdom', Applied Geography, Vol. 19, pp.123-136.
31. Tayanç, M. (2000) 'An assessment of spatial and temporal variation of sulfur dioxide levels over istanbul, turkey', Environmental Pollution, Vol. 107, pp.61-69.
32. Taylor, J.A., Jakeman, A.J. and Simpson, R.W. (1986) 'Modeling distributions of air pollutant concentrations-I. Identification of statistical models', Atmospheric Environment, Vol. 20, No. 9, pp.1781-1789.
33. Thompson, M.L., Reynolds, J., Cox, L.H., Guttorp, P. and Sampson, P.D. (2001) 'A review of statistical methods for the meteorological adjustment of tropospheric ozone', Atmospheric Environment, Vol. 35, pp.617-630.
34. Viotti, P., Liuti, G. and Di Geneva, P. (2002) 'Atmospheric urban pollution: applications of an artificial neural network (ANN) to the city of Perugia', Ecological Modelling, Vol. 148, pp.27-46.
35. Wang, W., Lu, W., Wang, X. and Leung, A.Y.T. (2003) 'Prediction of maximum daily ozone level using combined neural network and statistical characteristics', Environment International, Vol. 29, No. 5, pp.555-562.
36. Wang, X.G., Tang, Z., Tamura, H. and Ishii, M. (2004a) 'A modified error function for the backpropagation algorithm', Neurocomputing, Vol. 57, pp.477-484.
37. Wang, X.G., Tang, Z., Tamura, H., Ishii M. and Sun, W.D. (2004b) 'An improved backpropagation algorithm to avoid the local minima problem', Neurocomputing, Vol. 56, pp.455-460.
38. Yoon, S.W. and Lee, D.K. (2002) 'The development of the evaluation model of climate changes and air pollution for sustainability of cities in Korea', Landscape and Urban Planning, Vol. 960, pp. 1-16.
39. Zolghadri, A., Monsion, M., Henry, D., Marchionini, C. and Petrique, O. (2004) 'Development of an operational model-based warning system for tropospheric ozone concentrations in Bordeaux, France', Environmental Modelling and Software, Vol. 19, No. 4, pp.369-382.