Forecasting ozone peaks using self-organizing maps and fuzzy logic

被引：0
|
作者：
Glorennec, PY [1 ]
机构：
[1] IRIS, INSA Rennes, F-35043 Rennes, France
来源：
AIR POLLUTION MODELLING AND SIMULATION, PROCEEDINGS | 2002年
关键词：
Prediction; pollution; air quality; Kohonen maps; Fuzzy Inference Systems; missing data management; on-line or off-line learning;
D O I：
暂无
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
We present a Decision-Aided System for an early prediction (at 2:00 pm, in Universal Time) of ozone peaks for the next day. For better reliability, two tools are associated: a Kohonen Self-Organizing Map, for classification and immediate graphical visualization of the risk level, and a Fuzzy Inference System for sensor modeling. This system provides good results. Its main features are missing data management, characterization Of Situations just before a polluted day and prediction of the maximum value of an ozone sensor. The forecasting system can be used, using on-line learning, even in case of lack of historical data.
引用
收藏
页码：544 / 550
页数：7
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