World Library  


Add to Book Shelf
Flag as Inappropriate
Email this Book

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

By Nebot, A.

Click here to view

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
Historic
Publication Date:
2008
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

Description
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.

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

Excerpt
Abdul-Wahab, S. A. and Al-Alawi, S. M.: Assessment and prediction of tropospheric ozone concentration levels using artificial neural networks, Environ. Model. Softw., 17, 219–228, 2002.; Carvajal, R. and Nebot, A.: Growth model for white shrimp in semi-intensive farming using inductive reasoning methodology, Comput. Electron. Agr., 19, 187–210, 1998.; Cellier, F. E., Nebot, A., Mugica, F., and De Albornoz, A.: Combined qualitative/quantative simulation models of continuous-time processes using fuzzy inductive reasoning techniques, Int. J. Gen. Sys., 24(1–2), 95–116, 1995.; Chaloulakou, A., Assimacopoulos, D., and Lekkas, T.: Forecasting daily maximum ozone concentrations in the Athens Basin, Environ. Monit. Assess., 56, 97–112, 1999.; Chenevez, J. and Jensen, C. O.: Operational ozone forecast for the region of Copenhagen by the Danish Meteorological Institute, J. Atmos. Environ., 35, 4567–4580, 2001.; Comrie, A. C.: Comparing Neural Networks and Regression Models for Ozone Forecasting, Air and Waste Management, 47, 653–663, 1997.; Escobet, A., Nebot., A., and Cellier, F. E.: Visual-FIR as a tool for model identification and prediction of dynamical complex systems, Simul. Model. Pract. Th., 16, 76–92, 2008.; Ghiaus, C.: Linear fuzzy-discriminant analysis applied to forecast ozone concentration classes in sea-breeze regime, Atmos. Environ., 39, 4691–4702, 2005.; Gobierno del Distrito Federal (GDF): Informe de la calidad del aire y tendencias 2004 Zona Metropolitana de la Ciudad de México, 2005.; Peton, N., Dray, G., Pearson, D., Mesbah, M., and Vuillot, B.: Modelling and analysis of ozone episodes, Environ. Modell. Softw., 15, 647–652, 2000.; Gómez, P., Nebot, A., Ribeiro, S., Alquézar, R., Mugica, F., and Wotawa, F.: Local maximum ozone concentration prediction using soft computing methodologies, Syst. Anal. Model. Sim., 43(8), 1011–1031, 2003.; Gómez-Sanchis, J., Martín-Guerrero, J. D., Soria-Olivas, E., Vila-Francés, J., Carrasco, J. L., and del Valle-Tascón, S.: Neural networks for analysing the relevance of input variables in the prediction of tropospheric ozone conecntration, Atmos. Environ., 40, 6173–6180, 2006.; Heo, J. S. and Kim, D. S.: A new method of ozone forecasting using fuzzy expert and neural network system, Sci. Total Environ., 325, 221–237, 2004.; Klir, G. and Elias, D.: Architecture of Systems Problem Solving, 2nd Ed., Plenum Press, NY, 2002.; Koçak, K., Saylan, L., and Sen, O.: Nonlinear time series prediction of O3 concentration in Istanbul, Atmos. Environ., 34, 1267–1271, 2000.; Lengyel, A., Héberger, K., Paksy, L., Bánhidi, O., and Rajkó, R.: Prediction of ozone concentration in ambient air using multivariate methods, Chemosphere, 57, 889–896, 2004.; Lin, Y. and Cobourn, W. G.: Fuzzy system models combined with nonlinear regression for daily ground-level ozone predictions, J. Atmos. Environ., 41(16), 3502–3513, 2007.; Lu, W. Z., Wang, W. J., Wang, X. K., Yan, S. H., and Lam, J. C.: Potential assessment of a neural network model with PCA/RBF approach for forecasting pollutant trends in Mong Kok urban air, Hong Kong, Environ. Res., 96, 79–87, 2004.; Mintz, R., Young, B. R., and Svrcek, W. Y.: Fuzzy logic modeling of surface ozone concentrations, Comput. Chem. Eng., 29, 2049–2059, 2005.; Onkal-Engin, G., Demir, I., and Hiz, H.: Assessment of urban air quality in Istanbul using fuzzy synthetic evaluation, Atmos. Environ., 38, 3809–3815, 2004.; Morabito, F. C. and Versaci, M.: Fuzzy neural identification and forecasting techniques to process experimental urban air pollution data, Neural Networks, 16, 493–506, 2003.; Nebot, A., Mugica, F., Cellier, F., and Vallverd\'u, M.: Modeling and simulation of the central nervous system control with generic fuzzy models, Simulation, 79(11), 648–669, 2003.; Rohli, R. V., Hsu, S. A., Blanchard, B. W., and Fontenot, R. L.: Short-range prediction of tropospheric ozone concentrations and exceedances for Baton Rouge, Louisiana, Weather Forecas

 

Click To View

Additional Books


  • Quantification of the Impact in Mid-lati... (by )
  • Factors Influencing the Contribution of ... (by )
  • Fractional Release Factors of Long-lived... (by )
  • Columnar Modelling of Nucleation Burst E... (by )
  • Accuracy of Analyzed Temperatures, Winds... (by )
  • Spatial and Vertical Extent of Nucleatio... (by )
  • Impact of the North Atlantic Oscillation... (by )
  • Very Short-lived Bromomethanes Measured ... (by )
  • Sediment Records of Highly Variable Merc... (by )
  • Pesticides in the Atmosphere: a Comparis... (by )
  • Inferring Ozone Production in an Urban A... (by )
  • Arctic Clouds and Surface Radiation – a ... (by )
Scroll Left
Scroll Right

 



Copyright © World Library Foundation. All rights reserved. eBooks from World Library are sponsored by the World Library Foundation,
a 501c(4) Member's Support Non-Profit Organization, and is NOT affiliated with any governmental agency or department.