DocumentCode :
3011020
Title :
Meteorology-based forecasting of air quality index using neural network
Author :
Sharma, Mukesh ; Aggarwal, Sachin ; Bose, Purnendu ; Deshpande, Ashok
Author_Institution :
Dept. of Civil Eng., Indian Inst. of Technol., Kanpur, India
fYear :
2003
fDate :
21-24 Aug. 2003
Firstpage :
374
Lastpage :
378
Abstract :
Air quality index (AQI), a system for transforming air pollution levels into a single number, aims at providing information about air quality in simple terms to general public. Any advance information about AQI can forewarn the public of unhealthy air and encourage people to voluntarily reduce emissions-producing activities and avoid exposures to polluted environment. Two mathematical models (i) meteorology-based air quality level predictions and (ii) meteorology forecasting, have been developed (based on four year data) using neural network to forecast AQI for following three days. The AQI forecasting model was concluded as being satisfactory and useful for information dissemination to general public.
Keywords :
air pollution control; environmental science computing; information dissemination; neural nets; weather forecasting; air pollution levels; air quality index forecasting; emissions-producing activities; information dissemination; meteorology forecasting; meteorology-based air quality level predictions; neural network; Air pollution; Artificial neural networks; Atmospheric modeling; Couplings; Mathematical model; Meteorology; Neural networks; Predictive models; Weather forecasting; Wind forecasting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Informatics, 2003. INDIN 2003. Proceedings. IEEE International Conference on
Print_ISBN :
0-7803-8200-5
Type :
conf
DOI :
10.1109/INDIN.2003.1300360
Filename :
1300360
Link To Document :
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