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Artificial Neural Network based Vehicular pollution prediction model: A practical approach for urban air quality prediction
Published in
2010
Volume: 5
   
Issue: 3-4
Pages: 303 - 315
Abstract
The achievement of local air quality management goals in densely populated built-up urban areas often requires short-term air quality plans or emission management policies. Vehicular pollution modelling is an effective tool in managing the vehicular exhaust emissions in urban environments. In the recent past, Artificial Neural Network (ANN) based vehicular pollution models are found to be useful alternatives to conventional deterministic and stochastic based models in predicting vehicular pollutants dispersion. This paper compares the prediction performance of the ANN-based short-term vehicular pollution model with some frequently used conventional models using real-time data at one of the densely populated built-up areas in the city of Delhi, India. Copyright © 2010 Inderscience Enterprises Ltd.
About the journal
JournalInternational Journal of Environment and Waste Management
ISSN14789876
Open AccessNo
Concepts (24)
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    AIR QUALITY PLAN
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    Artificial neural network
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    BUILT-UP AREAS
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    Conventional models
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    DELHI , INDIA
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    EFFECTIVE TOOL
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    MANAGEMENT POLICY
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    POLLUTION MODELS
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    Prediction model
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    PREDICTION PERFORMANCE
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    Real-time data
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    Traffic
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    Urban air quality
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    URBAN AIR QUALITY MANAGEMENT
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    Urban areas
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    Urban environments
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    VEHICULAR EXHAUST EMISSIONS
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    Air quality
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    Forecasting
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    Neural networks
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    Pollution
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    Quality control
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    Stochastic models
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    Quality management