Operational forecasts of the geomagnetic Dst index
Operational forecasts of the geomagnetic Dst index
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DOI：
10.1029/2002gl016151
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发表时间：
2002-12
影响因子：
5.2
通讯作者：
H. Lundstedt;H. Gleisner;P. Wintoft
中科院分区：
文献类型：
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作者：
H. Lundstedt;H. Gleisner;P. Wintoft
本文提出一个地磁指数Dst的真实的时间预报模型。该模型由一个递归神经网络组成，该网络已被优化为尽可能小，而不会降低精度。它仅由太阳风磁场分量Bz、粒子密度n和速度V的小时平均值驱动，这意味着模型不依赖于观测到的Dst。在基于超过40，000小时的太阳风和Dst数据的评估中，该模型的误差小于目前使用的其他模型。该模型的完整描述见附录。
We here present a model for real time forecasting of the geomagnetic index Dst. The model consists of a recurrent neural network that has been optimized to be as small as possible without degrading the accuracy. It is driven solely by hourly averages of the solar wind magnetic field component Bz, particle density n, and velocity V, which means that the model does not rely on observed Dst. In an evaluation based on more than 40,000 hours of solar wind and Dst data, it is shown that this model has smaller errors than other models currently in operational use. A complete description of the model is given in an appendix.