Search results for "Surface ozone"
showing 3 items of 3 documents
Unbiased sensitivity analysis and pruning techniques in neural networks for surface ozone modelling
2005
Abstract This paper presents the use of artificial neural networks (ANNs) for surface ozone modelling. Due to the usual non-linear nature of problems in ecology, the use of ANNs has proven to be a common practice in this field. Nevertheless, few efforts have been made to acquire knowledge about the problems by analysing the useful, but often complex, input–output mapping performed by these models. In fact, researchers are not only interested in accurate methods but also in understandable models. In the present paper, we propose a methodology to extract the governing rules of trained ANN which, in turn, yields simplified models by using unbiased sensitivity and pruning techniques. Our propos…
The importance of stratospheric–tropospheric transport in affecting surface ozone concentrations in the western and northern tier of the United States
2011
Stratospheric–tropospheric exchange (STE) processes contribute at both high and low-elevation monitoring sites to background ozone (O3) concentrations. This study addresses the importance of stratospheric intrusions contributing to enhanced hourly average surface O3 concentrations (i.e., ≥50 ppb) at 12 O3 monitoring stations in the western and northern tier of the US for 2006, 2007, and 2008. The Lagrangian Analysis Tool (LAGRANTO) trajectory model identified specific days when stratosphere-to-troposphere transport was optimal to elevate surface O3 levels. The coincidences between the number of days with a daily maximum hourly average O3 concentration ≥ 50 ppb and stratosphere-to-tropospher…
Effective 1-day ahead prediction of hourly surface ozone concentrations in eastern Spain using linear models and neural networks
2002
The aim of this research was to develop pure predictive models in order to provide 24 h advance forecasts of the hourly ozone concentration for the rural site of Carcagente (Valencia, Spain) and the urban sites of Paterna (Valencia, Spain) and Alcoy (Alicante, Spain) over 4 years from 1996 to 1999. The peculiarity of the model presented here is that it uses past and previously predicted information of inputs exclusively, thus being this is the first genuine 24 h advance O3 predictive model with neural networks. We used autoregressive-moving average with exogenous inputs (ARMAX), multilayer perceptrons and FIR neural networks. Five performance measures yield reasonably good results in the th…