Prediction of ambient carbon monoxide concentration using nonlinear time series analysis technique

Transportation Research Part D: Transport and Environment

Volumn 12, Issue 8, 2007, Pages 596-600

  Chelani, A B ^a   Devotta, S ^a  

^a NATIONAL ENVIRONMENTAL ENGINEERING RESEARCH INSTITUTE   (India)

Author keywords

Local approximations; Neural networks; Nonlinear dynamics; Prediction horizon; Time series forecasting

Indexed keywords

APPROXIMATION THEORY; MATHEMATICAL MODELS; NEURAL NETWORKS; REGRESSION ANALYSIS; TIME SERIES ANALYSIS;

AUTOREGRESSIVE INTEGRATED MOVING AVERAGE MODEL; PREDICTION HORIZON;

CARBON MONOXIDE;

ARTIFICIAL NEURAL NETWORK; ATMOSPHERIC POLLUTION; CARBON MONOXIDE; CONCENTRATION (COMPOSITION); TIME SERIES ANALYSIS; URBAN AREA; URBAN POLLUTION;

EID: 35248870046     PISSN: 13619209     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.trd.2007.07.006     Document Type: Article

References (11)

1. Beale, M., 1997. MATLAB Users Guide (Ver 5.1). The Math Works Inc. Natick, MA.
2. Box G.E.P., and Jenkins G.M. Time series analysis, forecasting and control (1970), Holden-Day, San Francisco
3. Chen J.L., Islam S., and Biswas P. Nonlinear dynamics of hourly ozone concentrations: nonparametric short-term prediction. Atmospheric Environment 32 (1998) 1839-1848
4. Farmer D.J., and Sidorowich J.J. Predicting chaotic time series. Physics Review Letters 59 (1987) 85-848
5. Fox D.G. Judging air quality model performance. Bulletin of American Meteorological Society 62 (1981) 599-609
6. Fraser A.M., and Swinney H.L. Independent coordinates for strange attractors from mutual information. Physics Review A 33 (1986) 1134-1140
7. Grassberger P., and Procaccia I. Measuring strangeness of strange attractors. Physica D 9 (1983) 189-208
8. Kinnebrock, W. 1995. Neural networks - fundamental, applications, Examples, 2nd revised edition, Rolnberbourg Publishing House, Munich - Vienna.
9. Principe J.C., Rathie A., and Kuo J.M. Prediction of chaotic time series with neural networks and the issue of dynamic modeling. International Journal of Bifurcation and Chaos 2 (1992) 989-996
10. Raga G.B., and LeMoyne L. On the nature of air pollution dynamics in Mexico city - I, non linear analysis. Atmospheric Environment 30 (1996) 3987-3993
11. Takens F. Detecting strange attractors in turbulence. In: Rand D.A., and Young L.S. (Eds). Lecture Notes in Mathematics. Vol. 898 (1981), Springer, New York