基于综合信息模型的太阳活动预测方法* |
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作者姓名: | 秦磊 张灿 金会彬 |
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作者单位: | 1.中科院研究生院信息科学与工程学院,北京100049; 2信息安全国家重点实验室(中国科学院研究生院) ,北京100049;3中国科学院电子学研究所,北京100080 |
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摘 要: | 利用基于地磁活动指标型信息的统计先验类方法预测太阳活动周期峰值,是一种实用、有效的方法,但是利用此方法在对个别太阳活动周期的预测中出现较大误差,特别地,在对目前所处的第23太阳活动周期的预测中,误差超过30%。本文提出了利用多种信息综合预测太阳活动周期峰值的新方法,仿真实验表明,与基于地磁指标型信息的统计先验类方法比较,该新方法具有更好的适应性和稳定性,在对第23太阳活动周期的预测中,平均误差为10%。
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关 键 词: | 太阳活动周期 统计先验类方法 综合信息模型 峰值预测 |
Predictions of the sunspot numbers using synthesis information model |
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Authors: | Lei Qin Can Zhang Huibin Jin |
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Institution: | 1.School of Information Science and Engineering ,Graduate University , Chinese Academy of Sciences, Beijing 100049, China;2.State Key Laboratory of Information Security, Graduate University, Chinese Academy of Sciences, Beijing 100049, China;3.Chinese Academy of Sciences, Institute of Electronics, Beijing 100080, China |
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Abstract: | It’s usually considered to be practical and effective to predict the amplitude of solar cycle using statistical precursor methods based on the geomagnetic precursors, but it will appear biggish error in a certain cycle prediction by this method. Particularly, the error exceeds 30% in predicting the amplitude of the 23rd solar cycle, which we are now standing. This paper provides a synthesis prediction method based on multi-information. Computer simulation shows that the new method is more adaptive and stable, compared with the statistical precursor methods based on the geomagnetic precursors. In predicting the 23rd solar cycle amplitude, the average error is only 10%. |
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Keywords: | solar activity cycle statistical precursor methods synthesis information model prediction of the amplitude |
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