共查询到19条相似文献，搜索用时 109 毫秒
1.
太阳质子事件耀斑的短期预报 总被引：1，自引：1，他引：0
回顾产生太阳质子事件耀斑的短期预报,讨论短期预报在近期应做的研究。给出以下结论：（１）在６０年代和７０年代,质子事件耀斑的预报有相当大的进展;（２）新预报方法的探索和质子流在日冕与行星际的传播问题,是当前改进短期预报的关键;（３）对实际应用的短期预报工作的改进,可能需要从空间天气预报的角度,研究太阳活动区的分类。 相似文献
2.
太阳质子事件耀斑的短期预报 总被引：1，自引：0，他引：1
王家龙 《中国天文和天体物理学报》1999,(4)
回顾产生太阳质子事件耀斑的短期预报,讨论短期预报在近期应做的研究．给出以下结论：（１）在６０年代和７０年代,质子事件耀斑的预报有相当大的进展;（２）新预报方法的探索和质子流在日冕与行星际的传播问题,是当前改进短期预报的关键;（３）对实际应用的短期预报工作的改进,可能需要从空间天气预报的角度,研究太阳活动区的分类． 相似文献
3.
4.
朱翠莲 《中国天文和天体物理学报》2000,20(2)
以２２周太阳活动低年（１９９３－１９９５）质子事件及其对应活动区的综合分析结果为判据,预报２３周太阳活动上升阶段的质子事件．从１９９７年１１月开始到１９９８年１２月,用该方法预报的质子事件共６个,报准３个,不确定一个,虚报１个,漏报１个（太阳背面产生的事件）．本文对用该方法预报的结果进行了分析讨论,并与世界警报中心的预报结果进行了比对,结果表明,该方法对于质子事件的短期预报是有效的． 相似文献
5.
以２２周太阳活动低年（１９９３－１９９５）质子事件及其对应活动区的综合分析结果为判据,预报２３周太阳活动上升阶段的质子事件。从１９９７年１１月开始到１９９８年１２月,用该方法预报的质子事件共６个,报准３个,不确定一个,虚报１个,漏报１个（太阳背面产生的事件）。本对用该方法预报的结果进行了分析讨论,并与世界警报中心的预报结果进行了比对,结果表明,该方法对于质子事件的短期预报是有效的。 相似文献
6.
本文研究了1971－1980年间51个大于3％的宇宙线福布希下降对我国185个气象站上空雷暴活动的短期影响.结果表明，雷暴活动对福布希下降的短期响应存在明显的空间差异．在一些区域中福布希下降后雷暴活动明显增强，而在另一些区域中明显减弱，在这些明显响应区中，雷暴活动在福布希下降前后的差异显著性分别通过了10-2－10－6置信度检验．这些响应区所在的地理位置与雷暴活动对耀斑爆发的响应区相互对应，但响应性质恰恰相反．这些结果给太阳活动与地球短期天气相关机理研究提出了新的挑战，也为进一步的研究提供了新的事实根据． 相似文献
7.
《天文研究与技术》2004,1(4):312-315
恒星WUMa型相接双星的理论研究李立芳 ,张奉辉 (1) .1………………………………………银盘恒星运动学和化学丰度与银河系结构侯金良 ,陈力 ,常瑞香 ,孙振娜 (1) .16…………两类γ暴的谱形和光变曲线的统计差异彭朝阳 ,覃一平 (2 ) .77……………………………核塌缩超新星李宗伟 (3) .16 3…………………………………………………………………确定恒星表面有效温度的曲面拟合方法张健楠 ,吴福朝 ,罗阿理 ,赵永恒 (4 ) .2 4 9………太阳国内外空间天气短期预报和警报及其现状赵海娟 ,占腊生 ,戎永辉 (1) .2 8………………太阳耀斑 (后 )环… 相似文献
8.
针对广义回归神经网络用于日长变化预报过程中,样本的输入方式对预报结果的影响进行了研究。采用2种输入方式:即样本按不同跨度输入以及按连续输入,对日长变化进行预报。最终证明不同的样本输入方式对日长变化预报精度的影响较大,样本按跨度输入在超短期预报中预报精度较高,样本采用连续输入的方式在短期和中期预报中预报精度较高。 相似文献
9.
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
10.
就太阳质子事件预报研究的重要意义,产生太阳质子事件的太阳活动区的一般特征,质子耀斑的辐射特征,质子事件几个重要参数预报方法简述了目前的研究进展。还给出了当前为满足用户需要改进预报应着重研究的方面。 相似文献
11.
T. N. Chatterjee 《Monthly notices of the Royal Astronomical Society》2001,323(1):101-108
The prediction of a time series using a neural network involves an optimum state-space reconstruction. The state space of the daily 10.7-cm solar radio flux is reconstructed using an information theory approach. A multi-layer feed-forward neural net is used for short-term prediction of the time series. The convergence of the synaptic weights is obtained partially by simulated annealing and partially by the 'quick prop' variation of back-propagation. The result gives a reasonably accurate short-term prediction. 相似文献
12.
Solar flares are powered by the energy stored in magnetic fields, so evolutionary information of the magnetic field is important
for short-term prediction of solar flares. However, the existing solar flare prediction models only use the current information
of the active region. A sequential supervised learning method is introduced to add the evolutionary information of the active
region into a prediction model. The maximum horizontal gradient, the length of the neutral line, and the number of singular
points extracted from SOHO/MDI longitudinal magnetograms are used in the model to describe the nonpotentiality and complexity
of the photospheric magnetic field. The evolutionary characteristics of the predictors are analyzed by using autocorrelation
functions and mutual information functions. The analysis results indicate that a flare is influenced by the 3-day photospheric
magnetic field information before flare eruption. A sliding-window method is used to add evolutionary information of the predictors
into machine learning algorithms, then C4.5 decision tree and learning vector quantization are employed to predict the flare
level within 48 hours. Experimental results indicate that the performance of the short-term solar flare prediction model within
the sequential supervised learning framework is significantly improved. 相似文献
13.
《Physics and Chemistry of the Earth, Part C: Solar, Terrestrial & Planetary Science》1999,24(4):343-347
To test the ability and efficacy of neural networks in short-term prediction of ionospheric parameters, this study used the time series of the ionospheric foF2 data from Slough station during solar cycles 21 and 22. It describes different neural network architectures that led to similar conclusions on one-hour- ahead foF2 prediction. This prediction is compared with observations and results from linear and persistence models considered here as two special cases of the neural networks. 相似文献
14.
G.D. Parker 《Planetary and Space Science》1977,25(7):681-687
Variations of the ground-level nucleonic intensity and of indices of solar photospheric, chromospheric, and coronal activity at time scales of less than forty days show strong 27-day recurrent structure. Correlation functions for these time series suggest an origin for short-term modulation in impulsive solar activity. Flare-associated shocks originating in long-lived active zones fixed in solar longitude produce recurrent cosmic ray variations during 1964–1967, and corotating solar wind disturbances are of secondary importance to short-term modulation. 相似文献
15.
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
16.
Global changes of the solar activity can be expressed by the coronal index that is based upon the total irradiance of the coronal 530.3 nm green line from observations at five stations. Daily mean values of the coronal index of solar activity and other well-correlated solar indices are analyzed for the period 1966–1998 covering over three solar cycles. The significant correlation of this index with the sunspot number and the solar flare index have led to an analytical expression which can reproduce the coronal index of solar activity as a function of these parameters. This expression explains well the existence of the two maxima during the solar cycles taking into account the evolution of the magnetic field that can be expressed by some sinusoidal terms during solar maxima and minima. The accuracy between observed and calculated values of the coronal index on a daily basis reaches the value of 71%. It is concluded that the representative character of the coronal index is preserved even when using daily data and can therefore allow us to study long-term, intermediate and short-term variations for the Sun as a star, in association with different periodical solar–terrestrial phenomena useful for space weather studies. 相似文献
17.
The ability to predict the future behavior of solar activity has become extremely import due to its effect on the environment near the Earth.Predictions of both the amplitude and timing of the next solar cycle will assist in estimating the various consequences of space weather.The level of solar activity is usually expressed by international sunspot number (Rz).Several prediction techniques have been applied and have achieved varying degrees of success in the domain of solar activity prediction.We predict a... 相似文献
18.
《天文和天体物理学研究(英文版)》2021,(7)
Solar flare prediction plays an important role in understanding and forecasting space weather.The main goal of the Helioseismic and Magnetic Imager(HMI), one of the instruments on NASA's Solar Dynamics Observatory, is to study the origin of solar variability and characterize the Sun's magnetic activity.HMI provides continuous full-disk observations of the solar vector magnetic field with high cadence data that lead to reliable predictive capability; yet, solar flare prediction effort utilizing these data is still limited. In this paper, we present a machine-learning-as-a-service(MLaa S) framework, called Deep Sun,for predicting solar flares on the web based on HMI's data products. Specifically, we construct training data by utilizing the physical parameters provided by the Space-weather HMI Active Region Patch(SHARP)and categorize solar flares into four classes, namely B, C, M and X, according to the X-ray flare catalogs available at the National Centers for Environmental Information(NCEI). Thus, the solar flare prediction problem at hand is essentially a multi-class(i.e., four-class) classification problem. The Deep Sun system employs several machine learning algorithms to tackle this multi-class prediction problem and provides an application programming interface(API) for remote programming users. To our knowledge, Deep Sun is the first MLaa S tool capable of predicting solar flares through the internet. 相似文献
19.
We show that smoothed time series of 7 indices of solar activity exhibit significant solar cycle dependent differences in
their relative variations during the past 20 years. In some cases these observed hysteresis patterns start to repeat over
more than one solar cycle, giving evidence that this is a normal feature of solar variability. Among the indices we study,
we find that the hysteresis effects are approximately simple phase shifts, and we quantify these phase shifts in terms of
lag times behind the leading index, the International Sunspot Number. Our measured lag times range from less than one month
to greater than four months and can be much larger than lag times estimated from short-term variations of these same activity
indices during the emergence and decay of major active regions. We argue that hysteresis represents a real delay in the onset
and decline of solar activity and is an important clue in the search for physical processes responsible for changing solar
emission at various wavelengths.
The High Altitude Observatory is sponsored by the National Science Foundation. 相似文献