基于数据挖掘技术的金融信用决策管理系统

论文首先介绍了数据挖掘的概念及相关技术,然后论述了数据挖掘技术在金融信用决策管理系统中的应用,通过对预测解析、内在理解、决策建模、策略优化和策略精调的介绍,对数据挖掘的实现进行了有效描述.     

基于Traits泛化技术的SLE API编译码处理

在对CCSDS(Consultative Committee for Space Data Systems,空间数据咨询委员会)制定的SLE(Space Link Extension,空间链路扩展)的标准API(Application Program Interface,应用程序接口)设计开发过程中,需要对各种不同服务类型的操作进行ASN.1(Abstract Syntax Notation One,抽象语法标记1)编码译码,使用一般方法处理会存在大量的冗余且可扩展性不强。因此,设计了基于Traits技术的SLE API编码译码泛化模型,该模型从服务、协议数据单元、操作等3个层级,以及编码、译码这2个方向分别定义模板,并进行特化、偏特化以及萃取,从而实现了对编码、译码过程的泛化,并通过实例描述了应用过程。该模型有效提高了SLE API设计的灵活性、层次性、通用性,以及SLE服务的可拓展性。     

加工误差对压气机叶栅气动性能及稳定性影响的数据挖掘

为缓解加工误差影响评估过程中的"维数灾难",结合展向平均假设和基于高斯过程的Karhunen-Loève展开,提出了一种由法向加工误差导致的三维叶片表面几何不确定性降阶模型.通过给定加工误差分布的标准差函数求解几何不确定性降阶模型,并运用伪蒙特卡洛方法随机生成样本,最终训练人工神经网络预测了加工误差对高负荷直叶栅气动性...     

航天器电子信息数据流协同设计系统应用

航天器电子信息数据流涵盖了航天器遥测数据、遥控数据、内部通信数据及相关数据处理准则、数据传输协议等,是各种数据及其处理方法、协议的结合体。电子信息数据流设计过程涉及大量人员协同及迭代,均依靠文档作为主要传递方式,技术手段不足。本文提出一种航天器电子信息数据流协同设计系统,致力于数据源、设计工具、传递方式的统一,便于快速迭代中进行状态控制,实现全流程数字化传递,提高数据流总体设计能力和协同设计水平。     

基于OPC技术的LabVIEW与PLCs通讯

研究虚拟仪器软件LabVIEW与可编程控制器SLC500 PLC的数据接口技术。应用RSL inx通讯软件的OPC服务器和LabVIEW的Data Socket技术建立工作站与PLC的数据通信方式,为LabVIEW环境下PLC控制系统的动态监控提供一种通用方法。     

卫星研制中的接口数据管理

在卫星研制工作中可采用11种接口数据单加强设备的接口数据管理工作。它们是:机械特性,设备示意图,热特性,热特性示意图,电源功率,接口电特性,电气方块图,接插件表,接插件接点分配表,遥测表,遥控指令表。它们包含了可以全面反映设备接口特性的各项数据。使用它们可以进行严格的状态管理并保证接口数据协调工作的质量。文内介绍了这些数据单的具体内容以及使用中的问题。     

星载数据系统的结构

星载数据系统通过全星的计算机联网,建立统一数据管理,支持系统重组。文章探讨了星载数据系统结构的选择原则;并提出并行计算机系统的几种结构（如网格形和交叉开关网络）比目前使用的总线型结构更适合星载数据系统。     

Multi-sensor optimal data fusion for INS/GPS/SAR integrated navigation system

INS/GPS/SAR integrated navigation system represents the trend of next generation navigation systems with the high performance of independence, high precision and reliability. This paper presents a new multi-sensor data fusion methodology for INS/GPS/SAR integrated navigation systems. This methodology combines local decentralized fusion with global optimal fusion to enhance the accuracy and reliability of integrated navigation systems. A decentralized estimation fusion method is established for individual integrations of GPS and SAR into INS to obtain the local optimal state estimations in a parallel manner. A global optimal estimation fusion theory is studied to fuse the local optimal estimations for generating the global optimal state estimation of INS/GPS/SAR integrated navigation systems. The global data fusion features a method of variance upper finiteness and a method of variance upper bound to ensure that the global optimal state estimation can be achieved under a general condition. Experimental results demonstrate that INS/GPS/SAR integrated navigation systems achieved by using the proposed methodology have a better performance than INS/GPS integrated systems.     

Merged series of normalized water leaving radiances obtained from multiple satellite missions for the Mediterranean Sea

Merging time series of ocean color-derived products provided by independent satellite missions supports related biogeochemical and environmental applications by combining temporally overlapping data sets and by increasing data coverage. The creation of a merged series of normalized water leaving radiances _LWN$L_{\text{WN}}$, the primary ocean color product, is presented for the Mediterranean Sea using the SeaWiFS and MODIS data records. The merging relies on an optically-based technique that combines the available _LWN$L_{\text{WN}}$ signal in a spectrally consistent way. Validation statistics indicate uncertainties associated with the merged _LWN$L_{\text{WN}}$ decreasing from 23% at 412 nm to 12% in the 500- to 555-nm spectral range. The inter-comparison of the sensor-specific products, conducted at the scale of the basin for daily-to-monthly time scales, indicates an overall consistency. The level of differences varies with the wavelength considered and shows a marked seasonal cycle, with differences that tend to be higher in winter. The merged series is remarkably consistent with the sensor-specific data, with average absolute percent differences lower than 10% for all wavelengths below 555 nm. The benefit of merging in terms of sampling frequency over the basin is also illustrated. A merged series of _LWN$L_{\text{WN}}$ data based on the two considered missions provides valid data over 36% of the basin area on a daily basis.     

Advanced data acquisition system for SEVAN

Huge magnetic clouds of plasma emitted by the Sun dominate intense geomagnetic storm occurrences and simultaneously they are correlated with variations of spectra of particles and nuclei in the interplanetary space, ranging from subtermal solar wind ions till GeV energy galactic cosmic rays. For a reliable and fast forecast of Space Weather world-wide networks of particle detectors are operated at different latitudes, longitudes, and altitudes. Based on a new type of hybrid particle detector developed in the context of the International Heliophysical Year (IHY 2007) at Aragats Space Environmental Center (ASEC) we start to prepare hardware and software for the first sites of Space Environmental Viewing and Analysis Network (SEVAN). In the paper the architecture of the newly developed data acquisition system for SEVAN is presented. We plan to run the SEVAN network under one-and-the-same data acquisition system, enabling fast integration of data for on-line analysis of Solar Flare Events. An Advanced Data Acquisition System (ADAS) is designed as a distributed network of uniform components connected by Web Services. Its main component is Unified Readout and Control Server (URCS) which controls the underlying electronics by means of detector specific drivers and makes a preliminary analysis of the on-line data. The lower level components of URCS are implemented in C and a fast binary representation is used for the data exchange with electronics. However, after preprocessing, the data are converted to a self-describing hybrid XML/Binary format. To achieve better reliability all URCS are running on embedded computers without disk and fans to avoid the limited lifetime of moving mechanical parts. The data storage is carried out by means of high performance servers working in parallel to provide data security. These servers are periodically inquiring the data from all URCS and storing it in a MySQL database. The implementation of the control interface is based on high level web standards and, therefore, all properties of the system can be remotely managed and monitored by the operators using web browsers. The advanced data acquisition system at ASEC in Armenia was started in November, 2006. The reliability of the multi-client service was proven by continuously monitoring neutral and charged cosmic ray particles. Seven particle monitors are located at 2000 and 3200 m above sea level at a distance of 40 and 60 km from the main data server.