自适应神经网络预测对流层臭氧浓度

The 2011 International Joint Conference on Neural Networks Pub Date : 2011-10-03 DOI:10.1109/IJCNN.2011.6033450

Riccardo Taormina, L. Mesin, Fiammetta Orione, E. Pasero

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引用次数: 1

摘要

空气质量问题现在是全世界许多公民关心的主要问题。利用气象变量和大气污染物浓度时间序列可以进行局部空气质量预报。提出了一种基于人工神经网络(ANN)的自适应滤波技术，用于24小时最大日臭氧浓度预报。

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Forecasting tropospheric ozone concentrations with adaptive neural networks

The issue of air quality is now a major concern for many citizens worldwide. Local air quality forecasting can be made on the basis of meteorological variables and air pollutants concentration time series. We propose an adaptive filter technique based on an artificial neural network (ANN) to make 24-hours maximal daily ozone-concentrations forecasts.

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The 2011 International Joint Conference on Neural Networks

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