Forecasting of CO in an urban area by neural networks

被引：0
|
作者：
Pelliccioni, A
Pessa, E
机构：
[1] Italian Inst Occupat Safety & Hlth, Dept Environm, I-00184 Rome, Italy
[2] Univ Rome La Sapienza, Dipartimento Psicol, ECONA, InterUniv Res Ctr, I-00185 Rome, Italy
来源：
PHYSICA MEDICA | 1997年 / 13卷
关键词：
atmospheric pollutant forecasting; neural network; supervised learning; statistical distribution of data;
D O I：
暂无
中图分类号：
R8 [特种医学]; R445 [影像诊断学];
学科分类号：
1002 ; 100207 ; 1009 ;
摘要：
A 3-layer Perceptron neural network with Error Backpropagation learning rule has been used to forecast the concentration levels of CO and NO2 in Rome's urban center. The data came from measures of air atmospheric pollutant taken at the Arenula monitoring station in April 1993. A comparison was made between forecasting performances corresponding to different training sets and to different activation functions. The results obtained evidence how neural network performance is strongly dependent upon a right choice of function parameters, in turn related to the statistical features of data.
引用
收藏
页码：398 / 399
页数：2
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