Prediction of daily averaged PM10 concentrations by statistical time-varying model

Atmospheric Environment

Volumn 43, Issue 16, 2009, Pages 2579-2581

  Hoi, K I ^a   Yuen, K V ^a   Mok, K M ^a  

^a UNIVERSITY OF MACAU   (Macao)

Author keywords

Air quality prediction; Artificial Neural Network; Coastal city; Kalman filter; Macau; PM10

Indexed keywords

AIR QUALITY; BACKPROPAGATION ALGORITHMS; ERROR STATISTICS; FORECASTING; NEURAL NETWORKS;

AIR QUALITY PREDICTION; AUTO REGRESSIVE MODELS; COASTAL CITIES; LEVENBERG MARQUARDT BACKPROPAGATION; MACAU; PM10; STATISTICAL MODELING; TIME-VARYING MODELS;

KALMAN FILTERS;

AIR QUALITY; ARTIFICIAL NEURAL NETWORK; ATMOSPHERIC MODELING; ATMOSPHERIC POLLUTION; BACK PROPAGATION; COASTAL ZONE; ERROR ANALYSIS; KALMAN FILTER; PARTICULATE MATTER; PREDICTION; STATISTICAL ANALYSIS; TEMPORAL VARIATION;

AIR POLLUTION; AIR QUALITY; AIRBORNE PARTICLE; ALGORITHM; ARTICLE; METEOROLOGICAL PHENOMENA; PARTICLE SIZE; PRIORITY JOURNAL; SEASHORE; STATISTICAL MODEL;

ASIA; CHINA; EURASIA; FAR EAST; MACAU;

EID: 64549146639     PISSN: 13522310     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.atmosenv.2009.02.020     Document Type: Article

References (13)

1. Gardner M.W., and Dorling S.R. Artificial neural networks (the multilayer perceptron) - a review of applications in the atmosphere sciences. Atmospheric Environment 32 (1998) 2627-2636
2. Goyal P., Chan T., and Jaiswal N. Statistical models for the prediction of respirable suspended particulate matter in urban cities. Atmospheric Environment 40 (2006) 2068-2077
3. 10 hourly concentrations, in the Greater Area of Athens, Greece. Atmospheric Environment 40 (2006) 1216-1229
4. 10 concentrations in Belgium. Atmospheric Environment 39 (2005) 3279-3289
5. Hornik K., Stinchcombe M., and White H. Multilayer feedforward networks are universal approximators. Neural Network 2 (1989) 359-366
6. Jiang D., Zhang Y., Hu X., Zeng Y., Tan J., and Shao D. Progress in developing an ANN model for air pollution index forecast. Atmospheric Environment 38 (2004) 7055-7064
7. Kalman R.E. A new approach to linear filtering and prediction problems. Transactions of ASME, Journal of Basic Engineering 82 (1960) 35-45
8. Kalman R.E., and Bucy R.S. New results in linear filtering and prediction theory. Transactions of ASME, Journal of Basic Engineering 83 (1961) 95-107
9. Kermanshahi B. Design and Application of Neural Networks (1999), Shokodo, Tokyo (Chapter 3)
10. 2 concentration in Macau with artificial neural network. Energy and Buildings 28 (1998) 279-286
11. 2 concentration at a point with statistical approaches. Environmental Modelling & Software 19 (2004) 887-905
12. 2 concentrations in urban air in London. Atmospheric Environment 31 (1997) 4081-4094
13. Yuen K.V., Hoi K.I., and Mok K.M. Selection of noise parameters for Kalman filter. Journal of Earthquake Engineering and Engineering Vibration 6 (2007) 49-56