Forecasting tropospheric ozone concentrations with adaptive neural networks

被引：0

作者：

Taormina, R. ^{[2
]}

Mesin, L. ^{[1
]}

Orione, F. ^{[1
]}

Pasero, E. ^{[1
]}

机构：

[1] Politecn Torino, Dept Elect, Turin, Italy

[2] Hong Kong Polytech Univ, Dept Civil & Struct Engn, Hong Kong, Hong Kong, Peoples R China

来源：

2011 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN) | 2011年

关键词：

PREDICTION; POLLUTION;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：1857 / 1863

页数：7

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