第2009卡林顿周太阳活动的初步分析

介绍了第 2 0 0 9卡林顿周大黑子群AR484,AR486和AR488产生的太阳活动以及这些太阳活动对地球空间环境造成的影响。依据对太阳活动的统计研究 ,简要分析了三个大黑子群活动的差异。分析结果指出 ,关注某一时期太阳活动的活动经度带以及太阳活动在某一半球的主次是解决太阳活动短期预报非常重要的思路     

Application of support vector machine combined with K-nearest neighbors in solar flare and solar proton events forecasting

The support vector machine (SVM) combined with K-nearest neighbors (KNN), called the SVM-KNN method, is new classing algorithm that take the advantages of the SVM and KNN. This method is applied to the forecasting models for solar flares and proton events. For the solar flare forecasting model, the sunspot area, the sunspot magnetic class, and the McIntosh class of sunspot group and 10 cm solar radio flux are chosen as inputs; for the solar proton event forecasting model, the inputs include the longitude of active regions, the flux of soft X-ray, and those for the solar flare forecasting model. Detailed tests are implemented for both of the proposed forecasting models, in which the SVM-KNN and the SVM methods are compared. The testing results demonstrate that the SVM-KNN method provide a higher forecasting accuracy in contrast to the SVM. It also gives an increased rate of ‘Low’ prediction at the same time. The ‘Low’ prediction means occurrence of solar flares or proton events with predictions of non-occurrence. This method show promise for forecasting models of solar flare and proton events.     

近地轨道卫星的地影预报算法

针对传统地影预报算法计算量大,不适合星载计算机进行地影时刻自主预报的问题,提出一种地影预报星上算法。通过构造降维坐标系将卫星进出地影过程转换为“星-地-日”平面内的几何问题;基于常数变易法推导出阴影条件的隐式解析公式,其方程系数可由实时轨道参数确定。为简化计算,将星上算法设计为双层结构：构造迭代算法,依据实时轨道参数可精确预报卫星在每个节点上的地影时刻;而在任意两个节点之间采用解析算法进行近似预报。仿真结果表明,星上算法的预报精度高且计算量小,适合星载计算机进行地影时刻自主预报。     

Comparison of decision tree methods for finding active objects

The automated classification of objects from large catalogs or survey projects is an important task in many astronomical surveys. Faced with various classification algorithms, astronomers should select the method according to their requirements. Here we describe several kinds of decision trees for finding active objects by multi-wavelength data, such as REPTree, Random Tree, Decision Stump, Random Forest, J48, NBTree, AdTree. All decision tree approaches investigated are in the WEKA package. The classification performance of the methods is presented. In the process of classification by decision tree methods, the classification rules are easily obtained, moreover these rules are clear and easy to understand for astronomers. As a result, astronomers are inclined to prefer and apply them, thus know which attributes are important to discriminate celestial objects. The experimental results show that when various decision trees are applied in discriminating active objects (quasars, BL Lac objects and active galaxies) from non-active objects (stars and galaxies), ADTree is the best only in terms of accuracy, Decision Stump is the best only considering speed, J48 is the optimal choice considering both accuracy and speed.     

Solar activity prediction studies and services in NAOC

Solar activity prediction services started in 1960’s in National Astronomical Observatories, Chinese Academy of Sciences (NAOC). As one of the members of the International Space Environment Service (ISES), Regional Warning Center of China (RWC-China) was set up in 1990’s. Solar Activity Prediction Center (SAPC), as one of the four sub-centers of RWC-China, is located in NAOC. Solar activity prediction studies and services in NAOC cover short-term, medium-term, and long-term forecast of solar activities. Nowadays, certain prediction models, such as solar X-ray flare model, solar proton event model, solar 10 cm radio flux model, have been established for the practical prediction services. Recently, more and more physical analyses are introduced in the studies of solar activity prediction, such as the magnetic properties of solar active regions and magnetic structure of solar atmosphere. Besides traditional statistics algorithms, Machine Learning and Artificial Intelligence techniques, such as Support Vector Machine (SVM) method, are employed in the establishment of forecast models. A Web-based integrated platform for solar activity data sharing and forecast distribution is under construction.     

固体火箭发动机通用药柱的一维准定常内弹道计算

本文提出对任何药型都通用的一维准定常内弹道计算方法和与其相适用的药柱计算方法.解决了药柱和一维准定常内弹道计算的配合问题.用本程序对某实际发动机的内弹道性能进行了计算,将计算结果和用零维燃烧模型计算结果及热试车结果进行了比较.     

测控站点电磁兼容分析与预测技术研究

本文介绍了对测控站点内各测控设备的电磁干扰进行分析和预测的方法。系统采用干扰源与接收机逐对考虑的方式，极大简化了计算。并采用分阶段预测的方法，即分成：快速筛选、幅度筛选、频率筛选和详细预测四个阶段进行逐阶段分析和预测。     

数值模拟技术在热压罐工艺中的应用

随着复合材料和计算机技术的发展,数值模拟技术在复合材料工艺仿真中的应用也日益明显.总结分析了数值模拟技术在复合材料热压罐工艺中的研究进展,包括热压罐内流场仿真、固化放热控制、固化变形预测,以及热隔膜成型过程仿真的应用前景.随着大数据和复合材料自动化、智能化的发展,发展数值模拟技术是大势所趋.     

防空导弹任务规划与协同控制技术研究

针对防空导弹拦截群目标的任务需求，提出了多弹协同作战框架。考虑到实际拦截过程中弹目相对速度和角度较大的问题，建立了导弹拦截目标的能力预测模型，以确保分配结果处于导弹攻击能力范围内，并采用了改进的粒子群优化算法进行任务分配。然后为了兼顾协同制导和命中精度的要求，基于弹道成型和偏置比例导引的思想，结合一致性理论，设计了多弹时间/角度协同制导律。最后通过4枚导弹拦截3个目标的典型场景仿真，证明了方案的有效性。     

Study of Solar Corona in China

Considerable progress for the study of solar corona physics has been achieved by China's space physics community. It involves the theoretical study of coronal process of solar active phenomena, solar wind origin, acceleration of solar wind and coronal mass ejections, observational and numerical study of these problems and prediction methods of solar eruptive activities (such as flares/CMEs). Here is a brief summary of the progress in this area. Main progress is put upon the following three topics: corona and solar wind, numerical method, prediction method.