Computational Intelligence-based PM2.5 Air Pollution Forecasting

Computational intelligence based forecasting approaches proved to be more efficient in real time air pollution forecasting systems than the deterministic ones that are currently applied. Our research main goal is to identify the computational intelligence model that is more proper to real time PM2.5...

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Bibliographic Details
Published in:International journal of computers, communications & control communications & control, 2017-06, Vol.12 (3)
Main Authors: Oprea, Mihaela, Mihalache, Sanda Florentina, Popescu, Marian
Format: Article
Language:English
Subjects:
Adaptive systems
Air pollution
Air pollution forecasting
Air pollution measurements
Artificial intelligence
Artificial neural networks
Comparative studies
Correlation coefficient
Correlation coefficients
Forecasting
Fuzzy logic
Mathematical models
Neural networks
Particulate matter
Pollutants
Real time
Urban areas
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Summary:Computational intelligence based forecasting approaches proved to be more efficient in real time air pollution forecasting systems than the deterministic ones that are currently applied. Our research main goal is to identify the computational intelligence model that is more proper to real time PM2.5 air pollutant forecasting in urban areas. Starting from the study presented in [27]a, in this paper we first perform a comparative study between the most accurate computational intelligence models that were used for particulate matter (fraction PM2.5) air pollution forecasting: artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS). Based on the obtained experimental results, we make a comprehensive analysis of best ANN architecture identification. The experiments were realized on datasets from the AirBase databases with PM2.5 concentration hourly measurements. The statistical parameters that were computed are mean absolute error, root mean square error, index of agreement and correlation coefficient.
ISSN:1841-9836
1841-9844
DOI:10.15837/ijccc.2017.3.2907