Prediction of atmospheric pollution by particulate matter using a neural network

被引：0
|
作者：
Perez, P [1 ]
Trier, A [1 ]
Silva, C [1 ]
Montano, R [1 ]
机构：
[1] Univ Santiago Chile, Dept Fis, Santiago 2, Chile
来源：
PROGRESS IN CONNECTIONIST-BASED INFORMATION SYSTEMS, VOLS 1 AND 2 | 1998年
关键词：
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：
Based on data of particulate matter pollutants (PM2.5) recorded hourly for six months in the city of Santiago, we show that after filtering the noise, feedforward neural networks may be used in order to predict particle concentration in the atmosphere several hours in advance. The predictions with the neural net are better than those using an ARIMA model and persistence.
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页码：1000 / 1003
页数：4
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