两个组合恒等式的概率证明

给出了两个组合恒等式的概率证明，扩展了已知的结果。     

多传感器数据融合仿真平台的构建及设计

数据融合是军事C^3I系统的重要组成部分，对C^3I系统效能的发挥起着决定性的作用。文中简述了多传感器数据融合仿真平台的重要性及其实际意义，介绍了空中目标跟踪多传感器数据融合仿真平台的构建；针对位置级数据融合开发所需的模块，合理地进行了软件设计；仿真平台还通过使用模块化和开放性的结构，使仿真平台具有通用性、实时性和对话性等特点。最后，给出了一个该仿真平台的一个运行实例，使该仿真平台的可靠性、实用性等得到了仿真验证。     

输出/输入比值优势与DEA有效

进一步讨论了多目标规划模型 ( vp)中的 Pareto有效与 DEA有效的关系 ,得到两个重要结论 ,藉此无须求解 DEA模型就能判断某些 Pareto有效 DMU的 DEA有效性。     

Method for Risky Multiobjective Group Decision-Making and Its Application

The multiobjective group decision-making problem under risk is common in reality. This paper focuses on the study about risky multiobjective group decision-making problem where the index value is not certain. We give indexes classifying method and index normalizing formula of this type problem. By building objective function that minimizes general weighted distance from every alternative to the relatively best and worst alternative, the optimal membership degree of every decision-maker to every alternative can be obtained, and by building another objective function that minimizes general weighted distance from the optimal membership degree of every decision-maker to every alternative to the group optimal alternative and the group inferior alternative, the optimal membership degree of every decision-maker to every alternative can be obtained, which are both based on probability theory and fuzzy theory. Aftermost a model is established which collects group preferences. This method provides a new idea and     

雷达/红外双模制导背景下的模糊目标跟踪器

在雷达／红外双模制导背景下，对雷达／红外传感器的测量数据进行融合并提出了一种跟踪机动目标的模糊跟踪器。该跟踪器能够精确的获取目标机动的动态信息，应用一系列的模糊规则自适应的调整卡尔曼滤波器的过程噪声协方差矩阵，从而更适合用于实际的跟踪系统。通过对红外成像和雷达多传感器对目标跟踪系统的数字仿真表明所提出的模糊跟踪器性能良好。     

一种考虑补偿信用风险资本要求的算法

基于现行法定资本体制不考虑信用投资组合的多样化和限制空头信用风险头寸的补偿能力，设计了一种考虑补偿的信用风险资本要求的计算方法．该算法根据信用等级决定风险权重，可以更精确地测定信用风险资本．采用期限分段方法建立一个期间结构，区分当前和远期信用风险，考虑多头与空头信用风险头寸间的补偿．     

GPRS分组传输工业数据

结合工业监控软件技术的发展，用GPRS远距离实时传输生产数据，讨论了GPRS在工业监控中的优势和特点，以及建立起GPRS无线网络带来的传输速度、可靠性、拓扑结构以及安全性的问题。最后根据企业生产实际，提出一个工业监控平台网络设计方案。     

网络考试系统的安全设计

从对数据库系统的安全分析入手，结合网络考试系统的实际，从硬件系统、数据库系统、网络操作系统和网络应用程序几个方面，提出了解决网络考试系统安全性的方法。     

Discovering Frequent Subtrees from XML Data Using Neural Networks

By rapid progress of network and storage technologies, a huge amount of electronic data such as Web pages and XML has been available on Internet. In this paper, we study a data-mining problem of discovering frequent ordered sub-trees in a large collection of XML data, where both of the patterns and the data are modeled by labeled ordered trees. We present an efficient algorithm of Ordered Subtree Miner （OSTMiner） based on two- layer neural networks with Hebb rule, that computes all ordered sub-trees appearing in a collection of XML trees with frequent above a user-specified threshold using a special structure EM-tree. In this algo- rithm, EM-tree is used as an extended merging tree to supply scheme information for efficient pruning and mining frequent sub-trees. Experiments results showed that OSTMiner has good response time and scales well.