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Ozone Prediction Based on Meteorological Variables: a Fuzzy Inductive Reasoning Approach : Volume 8, Issue 3 (25/06/2008)

By Nebot, A.

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Book Id: WPLBN0003998159
Format Type: PDF Article :
File Size: Pages 28
Reproduction Date: 2015

Title: Ozone Prediction Based on Meteorological Variables: a Fuzzy Inductive Reasoning Approach : Volume 8, Issue 3 (25/06/2008)  
Author: Nebot, A.
Volume: Vol. 8, Issue 3
Language: English
Subject: Science, Atmospheric, Chemistry
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Escobet, A., Nebot, A., & Mugica, V. (2008). Ozone Prediction Based on Meteorological Variables: a Fuzzy Inductive Reasoning Approach : Volume 8, Issue 3 (25/06/2008). Retrieved from

Description: Universitat Politècnica de Catalunya, Barcelona, Spain. MILAGRO project was conducted in Mexico City during March 2006 with the main objective of study the local and global impact of pollution generated by megacities. The research presented in this paper is framed in MILAGRO project and is focused on the study and development of modeling methodologies that allow the forecasting of daily ozone concentrations. The present work aims to develop Fuzzy Inductive Reasoning (FIR) models using the Visual-FIR platform. FIR offers a model-based approach to modeling and predicting either univariate or multivariate time series. Visual-FIR offers an easy-friendly environment to perform this task. In this research, long term prediction of maximum ozone concentration in the downtown of Mexico City Metropolitan Area is performed. The data were registered every hour and include missing values. Two modeling perspectives are analyzed, i.e. monthly and seasonal models. The results show that the developed models are able to predict the diurnal variation of ozone, including its maximum daily value in an accurate manner.

Ozone prediction based on meteorological variables: a fuzzy inductive reasoning approach

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