共查询到17条相似文献，搜索用时 621 毫秒
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自1977年初我台λ3.2厘米射电望远镜投入工作后,我们就考虑如何将光学和射电观测资料一起用于太阳预报的综合方案中去。预报方案应该是简便而明确的,以便在值班人员有所变动时不影响预报的质量。1978年初,我们拟订了一项太阳活动综合指数以及相应的短期和中长期预报方案。 相似文献
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董士崙 《中国天文和天体物理学报》1984,(3)
本文简述了按权重综合几个预报结果的一般方法.通过1978—1980年我国进行重要试验期间太阳活动短期预报与实况的比较,计算了云南天文台、紫金山天文台和北京天文台综合的短波衰退(SWF)预报的标准差s_i;并由之确定了相应的权因子W_i. 相似文献
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《天文学报》2014,(4)
在低轨卫星的轨道计算中需要输入太阳辐射指数,它常用来描述太阳活动对高层大气密度的直接影响以及对轨道摄动的间接影响.因此太阳辐射指数的精度将影响轨道预报的精度.以太阳活动27 d短期震荡规律为基础,研究了一种利用135 d的辐射指数历史数据对F_(10.7)进行54 d中期预报的方法,能够预测太阳在未来2个自转周内辐射指数的变化.通过与其他预报方法的比较,表明:(1)该方法显著优于传统的三角函数长期预报法;(2)短期预报7 d时方法略优于美国空间天气预报中心(Space Weather Prediction Center,SWPC)的方法,RMS(Root Mean Square)下降约19%;(3)中期预报27 d时该方法与国内常用的54阶自回归模型精度基本相当,但方法的参数和需要的历史资料都明显减少,在轨道计算中使用更为简便,而且精度稳定,在54 d时预报值和实测值之间的相关系数仍然优于0.92.该方法的特点是只利用辐射指数较少的历史资料,不需要额外的太阳观测资料作支撑,能进行长达54 d的中期预报,为航天任务中的轨道中短期预报提供合理、可靠的辐射指数. 相似文献
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太阳活动区的模糊分类与活动性预测 总被引：2，自引：0，他引：2
运用模糊聚类分析的方法，研究太阳活动区特性。根据Hα、软X射线耀斑与黑子群各项特征因子的数据，进行标准化处理，分别运用模糊理论中的夹角余弦法，算术平均最小法进行标定，构造模糊相似矩阵与等价矩阵，根据模糊动态聚类分析方法，确定不同λ阈值，按照活动性强弱，对24个活动区进行分类。理论计算结果表明，不同等级类型的活动区强度预测与活动区实际活动性相一致，作为太阳活动水平预报，模糊聚类分析也是一种有效的方法。 相似文献
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《天文学报》2017,(3)
卫星钟差预报精度的不断提升是精密导航的关键问题.为了进一步提高钟差的预报精度和更好地反映钟差的变化特性,提出一种基于Takagi-Sugeno模糊神经网络(Fuzzy Neural Network,FNN)的钟差预报方法.该方法首先根据钟差数据的特点对钟差进行预处理,然后以预处理后的数据建立一种高精度预报钟差的Takagi-Sugeno模糊神经网络算法.采用IGS(International Global Navigation Satellite System Service)不同采样间隔的精密钟差数据进行了短期预报试验,并与ARIMA(Auto-Regressive Integrated Moving Average)模型、GM(1,1)模型及QP(Quadratic Polynomial)模型进行了对比试验,分析结果表明:对不同类型原子钟,该方法用于钟差短期预报是可行的、有效的,其获得的卫星钟差预报结果明显优于常规方法. 相似文献
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太阳日冕物质抛射特性的模糊分类研究 总被引：1，自引：0，他引：1
应用模糊集理论对日冕物质抛射（CME）特性进行分类研究，根据CME形态特性和特征因子之间的关系，重点阐明构造每个特性的隶属函数和确定权重因子的基本原理与方法，通过数据处理，对CME特性进行聚类分析，结果表明，模糊分类方法要优于传统的统计分析，对于CME特性按重要性分类，为空间环境的预报提供了一个具有实用价值的方法。 相似文献
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张勤 《中国天文和天体物理学报》1995,(1)
本文用非线性动力系统理论探讨了现代太阳周（１８５０年１月─１９９２年５月）黑子相对数月平均变化过程的可预报性。用时间延迟方法重构吸引子，计算它的最大Ｌｙａｐｕｎｏｖ指数（λ_１＝０．０２３±０．００４ｂｉｔｓ／月），估算了用这些黑子数进行确定性预报的理论时限（ｔ＝３．６±０．６年）．结果表明，动力系统的可预报性与它的最大Ｌｙａｐｕｎｏｖ指数有直接关系，黑子数月平均变化过程的演化不是周期的，也不是拟周期的，而是混沌的。即使今后找到了描述该过程的确定性方程，它的长期行为也不可能准确地预报，只能作短期预报，这是黑子数本身的混沌特性决定的。用于黑子数预报的纯粹数值统计方法仅对短期预报才有效。 相似文献
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F10.7太阳辐射通量作为输入参数被广泛运用于大气经验模型、电离层模型等空间环境模型,其预报精度直接影响航天器轨道预报精度.采用时间序列法统计了太阳辐射通量F10.7指数和太阳黑子数(SSN)的关系,给出了两者之间的线性关系,在此基础上提出了一种基于长短时记忆神经网络(Long and Short Term Memory,LSTM)的预报方法,方法结合了54 d太阳辐射通量指数和SSN历史数据来对F10.7进行未来7 d短期预报,并与其他预报方法的预报结果进行了比较,结果表明:(1)所建短期预报7 d方法模型的性能优于美国空间天气预报中心(Space Weather Prediction Center, SWPC)的方法,预测值和观测值的相关系数(CC)达到0.96,同时其均方根误差约为11.62个太阳辐射通量单位(sfu),预报结果的均方根误差(RMSE)低于SWPC,下降约11%;(2)对预测的23、24周太阳活动年结果统计表明,太阳活动高年的第7 d F10.7指数预报平均绝对百分比误差(MAPE)最优可达12.9%以内,低年最优可达2... 相似文献
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Shu-Rong Zhou Guang-Li Huang Zheng-Zhong Han Cheng Fang 《Astrophysics and Space Science》2002,280(4):369-380
In this paper, the theory and method of fuzzy mathematics are applied to forecast the activity of solar active regions. According
to the correlation between flares and several solar activity indices of active regions, the membership functions are constructed
to comprehensively evaluate and predict the activity of solar active regions. By means of data reduction and analysis, some
comparatively accurate results of prediction have been obtained. The accuracy of predicting the activity grades of active
regions is higher than 97%. This implies that the method of fuzzy forecast is a good one for solar activity prediction.
This revised version was published online in July 2006 with corrections to the Cover Date. 相似文献
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Hermann Schreiber 《Planetary and Space Science》1978,26(8):767-775
The linear Bartels ap indices, which by definition should have no average U.T. variations, show in fact two different average U.T. variations if the data is divided into two groups according to the two Interplanetary Magnetic Field (IMF) polarities. These differences are found to be similar for all seasons and activity ranges. Correlating the ap variations of individual days to the average ap variations for days with interplanetary away and toward polarities, a simple but objective precept of calculations is given to infer the IMF sector structure with a success rate of 73% of the days for the years 1963–1973. The same method is employed to infer the IMF sector structure since 1932, and the results are compared to the sector structure inferred from polar cap magnetograms. Some known features of solar sector fields, e.g. the heliographic latitude dependence of the dominant polarity, are also found in the polarity classification based on ap variations, whereas the significant higher geomagnetic activity during intervals of toward polarity before 1963, which was found in the sector structure inferred from polar cap magnetograms, is not observed. 相似文献
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本文对２２太阳活动用以来的中低纬冕洞和地磁指数Ａｐ进行了统计。对以月、季、年及２２周以来不同时段冕洞和地磁指数（Ｐｌａｎｅｔａｒｙ的Ａ指教）的时段合成图进行了分析。 相似文献
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M. G. Ogurtsov 《Solar physics》2005,231(1-2):167-176
Group sunspot number (GSN) values, averaged over decades, were reconstructed for a time interval 8505 BC–AD 1945 using data
on the concentration of radiocarbon in tree rings. The prediction of an average level of solar activity was made for the future
four decades by means of a nonlinear forecasting method. It was shown that the average activity of the Sun during 2005–2045
would be lower than at present. The given result is compared to the long-term forecasts by other authors. The importance of
a paleoastrophysical approach for obtaining a long-term solar prognosis and for revealing the basic characteristics of solar
activity change was confirmed. 相似文献
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A few prediction methods have been developed based on the precursor technique which is found to be successful for forecasting
the solar activity. Considering the geomagnetic activity aa indices during the descending phase of the preceding solar cycle as the precursor, we predict the maximum amplitude of annual
mean sunspot number in cycle 24 to be 111 ± 21. This suggests that the maximum amplitude of the upcoming cycle 24 will be
less than cycles 21–22. Further, we have estimated the annual mean geomagnetic activity aa index for the solar maximum year in cycle 24 to be 20.6 ± 4.7 and the average of the annual mean sunspot number during the
descending phase of cycle 24 is estimated to be 48 ± 16.8. 相似文献
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The variation in the length of day has complicated time-varying characteristics and the traditional method for linear time series analysis is always difficult to obtain good effect of prediction. If the non-linear artificial neural network technique is adopted to predict the variation in the length of day, the topological structure of the network model is determined by the least square error method. By taking into account the close relation between the variation in the length of day and the general circulation of atmosphere, the axial sequence of atmospheric angular momentum is introduced into the forecasting model of neural network. The results show that the forecast accuracy is significantly improved by taking advantage of the combination of the length of day and the atmospheric angular momentum sequence in comparison with the individual adoption of the data of the length of day. 相似文献