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Prediction of PM2.5 concentrations using fuzzy inductive reasoning in Mexico city

Author
Nebot, M.; Mugica, F.
Type of activity
Presentation of work at congresses
Name of edition
2nd International Conference on Simulation and Modeling Methodologies, Technologies and Applications
Date of publication
2012
Presentation's date
2012
Book of congress proceedings
Proceedings of the 2nd International Conference on Simulation and Modeling Methodologies, Technologies and Applications: Rome, Italy, 28-31 July, 2012
First page
527
Last page
533
Abstract
The research presented in this paper is focused on the study and development of fuzzy inductive reasoning models that allow the forecasting of daily particulate matter with diameter of 2.5 micrometres or less (PM2.5). FIR offers a model-based approach to modelling and predicting either univariate or multivariate time series. In this research, predictions of PM2.5 concentration at hour 12 of the next day, in the downtown of Mexico City Metropolitan Area, are performed. The data were registered ev...
Keywords
Air pollution prediction, Fuzzy inductive reasoning (FIR), PM2.5 pollution, Time series analysis
Group of research
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
SOCO - Soft Computing

Participants