On the prediction of solar activity using different neural network models

被引：0
|
作者：
Fessant, F [1 ]
Bengio, S [1 ]
Collobert, D [1 ]
机构：
[1] FRANCE TELECOM, CNET, LAB, RIO, TNT, F-22307 LANNION, FRANCE
来源：
ANNALES GEOPHYSICAE-ATMOSPHERES HYDROSPHERES AND SPACE SCIENCES | 1996年 / 14卷 / 01期
关键词：
D O I：
10.1007/s005850050265
中图分类号：
P1 [天文学];
学科分类号：
0704 ;
摘要：
Accurate prediction of ionospheric parameters is crucial for telecommunication companies. These parameters rely strongly on solar activity. In this paper, we analyze the use of neural networks for sunspot time series prediction. Three types of models are tested and experimental results are reported for a particular sunspot time series: the IR5 index.
引用
收藏
页码：20 / 26
页数：7
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