多阶段任务系统可靠性分析的二元决策图模型

为了实现计算机自动生成多阶段任务系统的二元决策图可靠性模型,提出了二元决策图可靠性建模的通用方法。定义了嵌套的二元决策图数据结构BDD_Element,给出了二元决策图模型的描述和存储方法,提出了与门、或门和k/n表决门向二元决策图模型的自动转化算法。给出了建立多阶段任务系统二元决策图可靠性模型的2个步骤:基于逻辑门转化算法,将部件逻辑关系结构函数转化为阶段二元决策图模型;基于二元决策图布尔操作规则整合阶段二元决策图模型。卫星姿态调整任务的可靠性分析表明:该方法可以有效应用于多阶段任务系统的可靠性分析。     

基于时序事件图的作战仿真溯因模型?

通过对作战仿真结果进行因果关系分析，可以加深对作战计划的理解，为指挥决策提供支持，是仿真的重要一环。为了能够对仿真结果进行因果关系分析，首先阐述了溯因和因果关系的概念，对支持溯因的仿真输出数据进行了需求分析，进而构建了以事件为核心描述单元的仿真输出数据模型；根据对事件图基本概念的理解，提出了基于时序事件图的溯因模型，最后给出了仿真输出数据映射为时序事件图的转化算法。     

基于不稳定性采样的主动学习方法

传统的主动学习方法往往仅基于当前的目标模型来挑选样本,而忽略了历史模型所蕴含的对未标注样本预测稳定性的信息。因此,提出基于不稳定性采样的主动学习方法,依据历史模型的预测差异来估计每个未标注样本对提高模型性能的潜在效用。该方法基于历史模型对样本的预测后验概率之间的差异来衡量无标注样本的不稳定性,并挑选最不稳定的样本进行查询。在多个数据集上的大量实验结果验证了方法的有效性。     

基于规则预置的应急事件指挥控制建模研究

为提高应急事件仿真过程中指挥控制模型的智能化程度和仿真结果的可信度,分析了应急事件指挥实体的指挥控制过程和指挥实体阃的信息交互关系,建立了基于预置规则的指挥控制模型,提出了驱动指挥控制模型运转的、表达应急事件指挥专业化知识的产生式指挥控制规则表达方式,重点研究了指挥控制规则的分类、定义和设计方法,并对该方法在仿真系统中的应用进行了分析,取得了比较理想的模拟效果.     

基于二元决策图的多阶段任务系统可靠性分析

分析了多阶段任务系统(PMS)可靠性分析中传统二元决策图(BDD)建模方法的不足,提出了一种将多阶段任务失效事件分解为互不相容的阶段失效事件,然后分别建立可靠性BDD模型的新方法。通过该方法建立的PMS可靠性BDD模型不但可以计算总体任务失效概率,同时也能计算任务在各阶段发生失效的概率。最后,给出了一个算例,验证了该算法的有效性。     

基于规则的域间路由系统异常检测

随着Internet的爆炸性增长,域间路由系统变得越来越复杂并难以控制,许多与域间路由安全相关的事件广泛引起了人们的关注。提出一个基于规则的域间路由监测框架,其中的规则可分为常规异常检测规则和特殊异常检测规则,它们能有效用于检测异常路由和可能的攻击行为,这两种规则的不同在于特殊异常检测规则是由大量路由得到的Internet模型来定义。研究了Internet层次模型与ISP商业关系模型的构造,基于这个框架实现了一个原型系统———ISP-Health,最后给出了检测能力结果。     

双机格斗行为建模方法研究

行为模型的真实性是决定CGF真实性的关键因素之一。针对双机格斗空战 ,提出了一种基于模糊规则的三层行为模型 ,并运用遗传算法对底层飞行状态模糊控制器进行了优化。文中给出了仿真实验结果。结果表明这种用模糊规则建立的行为模型产生了逼真的空战格斗行为。     

条件事件的表示

为了进行条件推理，本文讨论了条件事件的表示，并给出了相应的逻辑运算规则，引入了零事件间的概率比和多重条件事件的超条件事件概率的概念，它们均是无条件情形的推广。     

一种基于模糊控制的潜艇纯机动防御声自导鱼雷方法

潜艇防御反潜自导鱼雷是潜艇防御作战行动中的一个重要问题。从潜艇防御主动声自导鱼雷入手,采用模糊控制理论,通过建立语言值的隶属函数、模糊控制规则和模糊变换器以及给出响应动作这几个步骤,重点分析了潜艇从舷角入手结合模糊控制防御主动声自导鱼雷的方法,得到了潜艇纯机动法防御主动声自导鱼雷的模糊控制表,为潜艇防御主动声自导鱼雷提供了新的思路。     

主动代理技术在网管中的应用

文中首先介绍传统SNMP网络管理系统结构并指出其在管理大规模异构网络时存在的不足,然后引入主动网络技术并对其在网络管理方面的优势进行分析,在此基础上提出一种基于主动代理技术的网络管理模型。重点描述作为该模型核心部件的主动代理的实现方法,对用于实现各种网络管理功能的主动报文进行设计。最后,给出一个例子进一步说明主动报文的封装技术,并对该网管模型设计中的相关问题进行进一步阐述。     

基于再路由策略的保障网络性能可用性评估

以保障战争物流所需的保障网络为背景,基于面向任务的再路由策略,提出了保障网络性能可用性评估框架。以任务物流时延为例,研究了各种再路由策略下网络性能可用性指标的计算公式,绘制了时延曲线图,并作了对比分析。     

Designing a screening experiment for highly reliable products

Within a reasonable life‐testing time, how to improve the reliability of highly reliable products is one of the great challenges to today's manufacturers. By using a resolution III experiment together with degradation test, Tseng, Hamada, and Chiao (1995) presented an interesting case study of improving the reliability of fluorescent lamps. However, in conducting such an experiment, they did not address the problem of how to choose the optimal settings of variables, such as sample size, inspection frequency, and termination time for each run, which are influential to the correct identification of significant factors and the experimental cost. Assuming that the product's degradation paths satisfy Wiener processes, this paper proposes a systematic approach to the aforementioned problem. First, an intuitively appealing identification rule is proposed. Next, under the constraints of a minimum probability of correct decision and a maximum probability of incorrect decision of the proposed identification rule, the optimum test plan (including the determinations of inspection frequency, sample size, and termination time for each run) can be obtained by minimizing the total experimental cost. An example is provided to illustrate the proposed method. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 514–526, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10024     

矢量图形的知识获取与XML文档的智能生成

提出了一种从矢量图形中抽取出图元关联规则知识,利用正向知识推理来完成整个图形中图元的搜索,并获取各个图元信息智能生成文本信息的方法。这是一种通用的图文转换的智能生成方法,不同类型的矢量图形只需更换图元关联知识,都能利用知识推理方法智能生成XML(ExtensibleMarkupLanguage)文本。通过舰艇编队突击方案图转换成突击方案XML文本的实例进行了说明。     

动态拓扑图的卫星网络可视化方法

针对高度动态变化的卫星网络,提出一种基于动态拓扑图的可视化方法。动态拓扑图可视化的难点在于如何保持动态可视化过程中的稳定性,从而使用户容易地感知到网络中所发生的拓扑变化。根据卫星网络的动态变化特点,构建连续的动态拓扑图模型;设计一种保持布局稳定性的策略,并基于力引导思想提出一种动态拓扑图布局算法;以Iridium系统为典型实例,验证本文的可视化方法的合理性和可行性。实验表明,该方法能够以清晰的可视化图像支持用户对卫星网络动态拓扑的感知和理解。     

A novel facial emotion recognition scheme based on graph mining

Recent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. To reduce the number of generated sub-graphs, overlap ratio metric is utilized for this purpose. After encoding the final selected sub-graphs, binary classification is then applied to classify the emotion of the queried input facial image using six levels of classification. Binary cat swarm intelligence is applied within each level of classification to select proper sub-graphs that give the highest accuracy in that level. Different experiments have been conducted using Surrey Audio-Visual Expressed Emotion (SAVEE) database and the final system accuracy was 90.00%. The results show significant accuracy improvements (about 2%) by the proposed system in comparison to current published works in SAVEE database.     

浮筏隔振系统隔振器最佳布置方案研究

浮筏系统已经大量应用到舰船动力装置和其它设备的减振降噪中.运用导纳原理推导了双层减振装置隔振器对齐安装和不对齐安装方案的传递功率流,发现由于结构传递导纳小于输入导纳,不对齐安装更有利于降低宽频率振动的传递,并用有限元分析法实例验证了结论,为浮筏的优化设计和优化布置奠定了理论基础.     

The development and evaluation of a cost-based composite scheduling rule

A cost-based composite scheduling rule is developed and evaluated in comparison with three other well-researched scheduling rules—SPT, S/OPN, and SST. This cost rule permits the optimization of more than one performance measure at a time. The priority number that is used for scheduling operations through each machine group is based on four separate performance measures—(1) In-process Inventory, (2) Facilities Utilization, (3) Lateness, and (4) Mean Setup Time. The factorial experimental design involved three factor levels of loads, three factor levels of cost, and three factor levels of mean time. Analysis of variance was performed on each of the five output measures to study the effects of each of the three factors on each individual rule. Rank-order comparisons between rules were also made; and, finally, general conclusions with regard to the effectiveness and flexibility of the Cost Rule were drawn.     

The graph association problem: Mathematical models and a lagrangian heuristic

Graph association is the problem of merging many graphs that collectively describe a set of possibly repetitive entities and relationships into a single graph that contains unique entities and relationships. As a form of data association, graph association can be used to identify when two sensors are observing the same object so information from both sensors can be combined and analyzed in a meaningful and consistent way. Graph association between two graphs is related to the problem of graph matching, and between multiple graphs it is related to the common labeling of a graph set (also known as multiple graph matching) problem. This article contribution is to formulate graph association as a binary linear program and introduce a heuristic for solving multiple graph association using a Lagrangian relaxation approach to address issues with between‐graph transitivity requirements. The algorithms are tested on a representative dataset. The developed model formulation was found to accurately solve the graph association problem. Furthermore, the Lagrangian heuristic was found to solve the developed model within 3% of optimal on many problem instances, and found better solutions to large problems than is possible by directly using CPLEX. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

调度感知同步数据流建模

对流应用系统进行吞吐量分析需要将周期静态顺序调度建模到数据流图中,吞吐量分析效率依赖于数据流图的规模及建模时间。为了提高吞吐量分析效率,提出基于同构同步数据流图的调度感知同步数据流模型及相应建模方法。通过利用应用模型结构特征及周期静态顺序调度,可减少模型中的任务、边和初始符号数目;可以使用已有分析方法对模型进行吞吐量分析。实验结果表明,所提建模方法优于已有方法,可有效提高吞吐量分析效率。