PREDICTION OF MAJOR STORMS BY USING NEURAL NETWORKS
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摘要: 本文采用阈值预报的策略和人工神经网络BP模型,以13个太阳风参量和地磁AE,Dst指数作为输入,以0或1作为输出,提前4h预报大磁暴主相发生的时刻.结果表明,采用神经网络方法的阈值预报可以对灾害性磁暴的发生提前数小时做出比较准确的预报.Abstract: Good prediction results for geomagnetic indices have been obtained with the use of artificial intelligent(AI)technique,especially by the neural networks.While a common Problem is how to increase the advance time of the prediction.It is true that the earlier of the prediction, the less possibility to predict the detail of an impending event.Therefore threshold prediction should be also a very helpful and useful method for early time prediction when forecasting the occurrence of the events which bring disaster on the cormmunication,power transmission and satellite life etc. Threshold prediction means the predicted events are over a threshold,such as-120nT. In this paper BP model of neural networks is used to predict the major storms 4 hours ahead, with the minimum of Dst less than-120nT. The inputs are 13 solar wind parameters and geomagnetic AE and Dst.The ought is I for major storms or 0 for non major storms. The results show that the threshold prediction by neural networks can give accurate prediction for major storm occurrence.
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Key words:
- Neural networks /
- Prediction /
- Magnetic storm
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