Back to Search
Start Over
Development and comparative analysis of tropospheric ozone prediction models using linear and artificial intelligence-based models in Mexicali, Baja California (Mexico) and Calexico, California (US)
- Source :
- RIUR. Repositorio Institucional de la Universidad de La Rioja, instname
- Publication Year :
- 2008
-
Abstract
- This study developed 12 prediction models using two types of data matrix (daily means and a selection of the mean for the first 6 h of the day). The Persistence parametric prediction technique was applied separately to these matrices, as well as semiparametric Ridge Regression and three non-parametric or artificial intelligence techniques: Support Vector Machine, Multilayer Perceptron and ELMAN networks. The target was the prediction of maximum tropospheric ozone concentrations for the next day in the Mexicali-Calexico border area. The main ozone precursors and meteorological parameters were used for the different models. The proposals were evaluated using specific performance measurements for the air quality models established in the Model Validation Kit and recommended by the US Environmental Protection Agency. Results with similar margins of error were obtained in various models developed in this study, and some of them have provided smaller margins of error than similar prediction models existing in the literature developed in other regions. For this reason, we consider it feasible to apply the prediction models developed and they could be useful for supporting decisions in the matter of ozone pollution in the region under study, as well as for use in daily forecasting in this area. © 2007 Elsevier Ltd. All rights reserved.
- Subjects :
- Engineering
Ridge Regression
Environmental Engineering
Support Vector Machine
Meteorology
Ozone neural network modeling
Data type
Model Validation Kit (MvK)
chemistry.chemical_compound
ELMAN neural network
US-Mexico border
Tropospheric ozone
Air quality index
Parametric statistics
business.industry
Multilayer Perceptron (MLP)
Ecological Modeling
Transboundary air quality
Regression
Support vector machine
chemistry
Multilayer perceptron
Artificial intelligence
business
Software
Predictive modelling
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- RIUR. Repositorio Institucional de la Universidad de La Rioja, instname
- Accession number :
- edsair.doi.dedup.....b07e506d87d8c2099c508edaf48f82a0