International audienceA neural network combined to a neural classifier is used in a real time forecasting of hourly maximum ozone in the centre of France, in an urban atmosphere. This neural model is based on the MultiLayer Perceptron (MLP) structure. The inputs of the statistical network are model output statistics of the weather predictions from the French National Weather Service. With this neural classifier, the Success Index of forecasting is 78% whereas it is from 65% to 72% with the classical MLPs. During the validation phase, in the Summer of 2003, six ozone peaks above the threshold were detected. They actually were seven
A neural network model to predict ozone concentration in the Sao Paulo Metropolitan Area was develop...
A neural network model to predict ozone concentration in the Sao Paulo Metropolitan Area was develop...
The aim of the present work is to provide a methodological procedure to forecast Ozone concentration...
International audienceA neural network combined to a neural classifier is used in a real time foreca...
International audienceA neural network combined to a neural classifier is used in a real time foreca...
International audienceA neural network combined to a neural classifier is used in a real time foreca...
International audienceA neural network combined to a neural classifier is used in a real time foreca...
International audienceA neural network combined to a neural classifier is used in a real time foreca...
International audienceA neural network combined to a neural classifier is used in a real time foreca...
Artificial neural networks (ANNs) are well suited to solve complex and highly non-linear problems. V...
Atmospheric pollutants concentration forecasting is an important issue in air quality monitoring. Qu...
Artificial neural networks (ANNs) are well suited to solve complex and highly non-linear problems. V...
Tropospheric (ground-level) ozone has adverse effects on human health and environment. In this study...
The prediction of near-surface ozone concentrations is important to support regulatory procedures fo...
A neural network model to predict ozone concentration in the Sao Paulo Metropolitan Area was develop...
A neural network model to predict ozone concentration in the Sao Paulo Metropolitan Area was develop...
A neural network model to predict ozone concentration in the Sao Paulo Metropolitan Area was develop...
The aim of the present work is to provide a methodological procedure to forecast Ozone concentration...
International audienceA neural network combined to a neural classifier is used in a real time foreca...
International audienceA neural network combined to a neural classifier is used in a real time foreca...
International audienceA neural network combined to a neural classifier is used in a real time foreca...
International audienceA neural network combined to a neural classifier is used in a real time foreca...
International audienceA neural network combined to a neural classifier is used in a real time foreca...
International audienceA neural network combined to a neural classifier is used in a real time foreca...
Artificial neural networks (ANNs) are well suited to solve complex and highly non-linear problems. V...
Atmospheric pollutants concentration forecasting is an important issue in air quality monitoring. Qu...
Artificial neural networks (ANNs) are well suited to solve complex and highly non-linear problems. V...
Tropospheric (ground-level) ozone has adverse effects on human health and environment. In this study...
The prediction of near-surface ozone concentrations is important to support regulatory procedures fo...
A neural network model to predict ozone concentration in the Sao Paulo Metropolitan Area was develop...
A neural network model to predict ozone concentration in the Sao Paulo Metropolitan Area was develop...
A neural network model to predict ozone concentration in the Sao Paulo Metropolitan Area was develop...
The aim of the present work is to provide a methodological procedure to forecast Ozone concentration...