我国人口受教育程度分类模型

模糊聚类分析是研究将事物进行分类的科学,其目的是利用一定的数学方法将研究的样品或变量归并为若干类,使得每一类中的所有个体之间具有密切的关系,而不同类之间个体关系相对比较疏远。本文用模糊聚类方法将我国人口受教育程度分成了四类的模式,按该模式可以对其他省市进行了预测分类。     

一种基于内容的图像数据库聚类算法

本文分析了数据库信息检索的索引算法,并且对k-means聚类算法中初始聚类数目和聚类中心的设定进行了改进,设计了一种用于大容量图像数据库的索引方法。     

高密度高强度丁羟推进剂配方及工艺性研究

介绍了高密度、高强度丁羟推进剂的研制。采用一种被称为STR的活性基增强剂来增强HTPB、TDI粘合剂体系的固化网络。用不同含量Cu、Cr、Pb、Fe离子进行压强指数调节,优化了粒度级配,使推进剂具有如下优良特性:固体含量>89%、密度达到1.84g/cm3、20℃抗拉强度σm≈4MPa、良好的工艺性和流变性能、并且在70℃高温下贮存2a力学性能无明显下降。     

基于排队论指导的K-Means聚类算法及其在TTC网络优化设计中的应用

提出了一种在K-Means算法基础上改进的聚类算法QSKM,对网络结点分组进行优化设计。我们利用排队论对网络通信中的呼叫与处理进行分析,确定最少分组数,作为K-Means聚类算法的初试K值,由此作为聚类算法的起点,对交换机数量、空间布局以及网络结点分组进行设计。通过对QSKM算法和传统K-Means算法的计算复杂度进行分析比较以及QSKM算法在北京航天飞行控制中心显示网络设计中的应用研究表明,QSKM算法是有效的,降低了传统K-Means算法的计算复杂度。在我们设计的QSKM算法中,排队论可以为K-Means聚类运算中K的初始选取提供指导,聚类算法利用网络特征对基于排队论的网络设计方法进行完善,从而得到最佳的网络分布方案。     

自适应时间平滑的演化谱聚类

传统的聚类算法一般只适用于静态数据的处理,而真实世界的数据往往数据量大且变化多,静态的聚类算法不能为动态数据提供其演化规律的分析学习。演化数据的聚类,一方面要正确反映每一时刻数据的合理簇划分,另一方面又要使动态的聚类结果在演化过程中尽可能平滑。本文提出了一种自适应时间平滑的演化聚类框架,该模型考虑到当前时刻数据与历史时刻数据的未知关联,通过限定时间回溯的范围,自适应地寻找与当前快照最相关的历史快照,并通过有机融合基于Itakura-Saito距离的静态相似度和基于时间序列的动态相似度,计算各个时间片快照上的相似度矩阵。本文进一步提出了两种自适应时间平滑的演化谱聚类算法,从不同的角度定义时间代价,得到不同的演化聚类结果。在真实数据集上的实验表明这两种算法能够有效地利用历史数据,在聚类结果上准确性更高,时间平滑性也更好。     

Comparison of the CHAMP radio occultation data with the Canadian advanced digital ionosonde in the Polar Regions

In this paper we present the results of the comparison of the retrieved electron density profiles of the Ionospheric Radio Occultation (IRO) experiment on board CHAMP (CHAllenging Minisatellite Payload), with the ground ionosonde profiles for the Polar Regions. IRO retrieved electron density profiles from CHAMP are compared with Canadian Advanced Digital Ionosonde (CADI) measurements at two vertical sounding stations well within the Polar Cap, Eureka (geog. 80°13′ N; 86°11′ W) and Resolute Bay (geog. 74°41′ N; 94°54′ W). We compared the ionospheric parameters such as the peak electron density of the F-layer (NmF₂) and the peak height of the F-layer (h_mF₂) for a 3-year period, 2004–2006. CHAMP derived NmF₂ shows reasonable agreement with the ionosonde retrieved NmF₂ for both the stations (0.76 and 0.71 correlation coefficient, for Eureka and Resolute Bay, respectively) whereas the h_mF₂ agreement is not that acceptable (0.25 and 0.37 correlation coefficient, respectively). The h_mF₂ from vertical sounding showed less spread than the CHAMP h_mF₂.     

Evaluation of the IRI-2007 model options for the topside electron density

The International Reference Ionosphere (IRI) 2007 provides two new options for the topside electron density profile: (a) a correction of the IRI-2001 model, and (b) the NeQuick topside formula. We use the large volume of Alouette 1, 2 and ISIS 1, 2 topside sounder data to evaluate these two new options with special emphasis on the uppermost topside where IRI-2001 showed the largest discrepancies. We will also study the accurate representation of profiles in the equatorial anomaly region where the profile function has to accommodate two latitudinal maxima (crests) at lower altitudes but only a single maximum (at the equator) higher up. In addition to IRI-2001 and the two new IRI-2007 options we also include the Intercosmos-based topside model of Triskova, Truhlik, and Smilauer [Triskova, L., Truhlik, V., Smilauer, J. An empirical topside electron density model for calculation of absolute ion densities in IRI. Adv. Space Res. 37 (5), 928–934, 2006] (TTS model) in our analysis. We find that overall IRI-2007-NeQ gives the best results but IRI-2007-corrected provides a more realistic representation of the altitudinal–latitudinal structure in the equatorial anomaly region. The applicability of the TTS model is limited by the fact that it is not normalized to the F2 peak density and height.     

Wavelet modelling in support of IRI

The slant total electron content (STEC) of the ionosphere is defined as the integral of the electron density along the ray-path of the signal between the transmitter and the receiver. So-called geometry free GPS measurements provide information on the electron density, which is basically a four-dimensional function depending on spatial position and time. Since ground-based measurements are not very sensitive to the vertical structure within the atmosphere, the ionosphere is often represented by a spherical layer, where all electrons are concentrated. Then the STEC is transformed into the vertical total electron content (VTEC), which is a three-dimensional function depending on longitude, latitude and time.In our approach, we decompose an ionospheric function, i.e. the electron density or the VTEC, into a reference part computed from a given model like the International Reference Ionosphere (IRI) and an unknown correction term expanded in a multi-dimensional series in terms of localizing base functions. The corresponding series coefficients are calculable from GPS measurements applying parameter estimation procedures. Since the GPS receivers are located rather unbalanced, finer structures are modelable just in regions with a sufficient number of observation sites. Due to the localizing feature of B-spline functions we apply a tensor product spline expansion to model the correction term regionally. Furthermore, the multi-resolution representation derived from wavelet analysis allows monitoring the ionosphere at different resolutions levels. We demonstrate the advantages of this procedure by representing a simulated VTEC data set over South America.     

An empirical model of electron density in low latitude at 600 km obtained by Hinotori satellite

An empirical model of electron density (Ne) was constructed by using the data obtained with an impedance probe on board Japanese Hinotori satellite. The satellite was in circular orbit of the height of 600 km with the inclination of 31 degrees from February 1981 to June 1982. The constructed model gives Ne at any local time with the time resolution of 90 min and between −25 and 25 degrees in magnetic latitude with its resolution of 5 degrees in the range of F_10.7 from 150 to 250 under the condition of K_p < 4. Spline interpolations are applied to the functions of day of year, geomagnetic latitude and solar local time, and linear interpolation is applied to the function of F_10.7. Longitude dependence of Ne is not taken into account. Our density model can reproduce solar local time variation of electron density at 600 km altitude better than current International Reference Ionosphere (IRI2001) model which overestimates Ne in night time and underestimates Ne in day time. Our density model together with electron temperature model which has been constructed before will enable more understanding of upper ionospheric phenomenon in the equatorial region.