基于贝叶斯网络的空中目标威胁估计算法

联合作战条件下,指挥决策人员在海量描述战场态势的数据和信息面前往往会束手无策,无法快速作出正确的决策。贝叶斯网络模型是一种基于概率推理的网络化数学模型,能够通过一些变量的信息来获取其他的概率信息,从而解决不定性和不完整性问题。提出了一种基于贝叶斯网络的空中目标威胁估计算法,用空中威胁网络模型找到空中威胁目标各属性之间的潜在关系,并建立空中目标威胁估计算法,最后以一个实例来验证该空中目标威胁估计的计算过程和有效性。     

高性能互连网络中端口阻塞故障预测方法

随着系统规模、芯片功耗和链路速率的提升,高性能互连网络的整体故障率也不断上升,传统运维方式将难以为继,给高性能计算系统整体可靠性和可用性带来了巨大挑战。针对网络端口阻塞这类严重网络故障,提出无监督算法的预测模型。该模型从历史信息中挖掘征兆性规律并形成新的特征向量,应用K-means聚类算法对特征向量进行学习归类。在预测时,结合端口当前状态,利用二次指数平滑算法对未来状态进行预测,将得到的新特征向量使用K-means算法预判是否会发生阻塞故障。利用拓扑结构信息,分别对叶交换机和根交换机构建预测子模型,进而提升预测的精确率。结果表明,该预测模型能保持在召回率为88.2%的前提下,达到65.2%的准确率,可为运维人员提供有效的辅助。     

Countering Insurgents through Distributed Operations: Insights from Malaya 1948–1960

This article examines the emerging US Marine Corps concept of ‘Distributed Operations’ (DO) and its applicability to counter-insurgency. DO involves dispersing the force and empowering decentralised units so as to create a network of mobile, agile and adaptable cells, each operating with a significant degree of autonomy yet in line with the commander's overall intent. This concept's applicability to irregular campaigns is assessed with reference to the Malayan Emergency, in which the British and Commonwealth forces employed dispersed and decentralised small-unit formations to great effect. The article teases out the conditions that allowed DO to succeed in Malaya, and comments on the requirements and implications for the use of DO today in the prosecution of the ‘Long War’.     

一种基于视觉的目标舷角实时测量方法

舰船的舷角是鱼雷攻击时的重要参数,同时也是海航避碰中避碰线路确定的计算依据。在基于视觉的识别中,获取目标舰船的舷角即可确定其相对拍摄视角,从而大大缩小在全方位视野特征库中的搜索范围,提高识别速度。然而现有的舷角测量方法均是采用连续跟踪解算实现的,无法实时测量。为解决实时测量的问题,首先推导了基于视觉的目标舰船舷角测量原理,然后针对摄像机倾斜的情况提出基于水天线校正的改进方法,最后通过实验验证,结果表明方法简单易操作、实时性好。     

影响指挥员军事决策的因素分析

现代高技术条件下的局部战争,军事活动的节奏明显加快,作战空间跨域扩展,战场态势复杂多变,尤其是当重大危机发生时,对军事决策的时效性提出了更高要求,指挥员必须能够及时、果断、有效、准确地定下作战决心。指挥员军事决策的有效性不仅受主观因素的影响,还受客观因素的影响。通过对影响因素的分析,提出提高指挥员军事决策能力的有效途径,为军队指挥人才培养提供合理建议。     

基于混合数据挖掘模型预测用户流失

用户流失预测问题广泛应用在银行、金融、电信等多种领域。对用户行为进行有效的预测和分析有助于企业的竞争和了解瞬息万变的市场规律。采用3种混合的数据挖掘模型对用户流失问题进行了研究,以形成一个准确高效的用户流失预测模型。这3种模型应用于数据挖掘的两个阶段:聚类阶段和预测分析阶段。在第1阶段中,对用户的数据进行过滤。第2阶段对用户行为进行预测。第1个模型采用了二分k-means算法进行数据过滤和多层感知人工神经网络(MLP-ANN)相结合进行预测。第2个模型采用层次化聚类与MLP–ANN相结合进行预测。第3个模型使用自组织映射(Self-Organizing Maps)与MLP-ANN进行预测。这3种模型预测分析基于真实数据,用户流失率采用3种模型混合计算的方式得出结果并同真实值进行比较。分析结果表明采用多模型的混合数据挖掘模型的数据准确度优于普通的单一模型。     

一种空中目标的不确定性威胁程度预测模型

目标威胁预测是对空态势和威胁估计的重要内容.针对空中目标飞行控制的基本特点,建立了基于经验公式的空中目标不确定性位置预测模型,进一步推导了不确定性威胁概率预测的模型和实用算法.仿真结果证明了模型的有效性,可用于多类空中目标意图推理及威胁判断.     

South Africa's threat environment: a guide for the National Planning Commission

Abstract

The mandate of South Africa's recently appointed National Planning Commission includes addressing ‘defence and security matters’. This article seeks to outline the central elements of the threat environment facing South Africa in the foreseeable future. It is argued that South Africa faces no meaningful existential threat from conventional military forces but that its security forces will need to be prepared to address possible raids and attacks by conventional military forces both on home soil and on vital interests beyond the nation's borders. Other threats highlighted include the threats posed by potential insurgencies, by terrorism, and by crime, social unrest and banditry. Also addressed is the danger of so-called hybrid threats, in which two or more of the single threat types outlined here are combined. Finally, the article challenges the National Planning Commission to rethink South Africa's policy on peace operations in the light of the need to ensure the safety and security of the nation's citizenry.     

Attacking the Atom: Does Bombing Nuclear Facilities Affect Proliferation?

Abstract

What are the consequences of military strikes against nuclear facilities? In particular, do they ‘work’ by delaying the target states ability to build the bomb? This article addresses these questions by conducting an analysis of 16 attacks against nuclear facilities from 1942 to 2007. We analyze strikes that occurred during peacetime and raids that took place in the context of an ongoing interstate war. The findings indicate that strikes are neither as uniformly fruitless as the skeptics would suggest, nor as productive as advocates have claimed. There is evidence that the peacetime attacks delayed the target's nuclear program, although the size of this effect is rather modest. The wartime cases were less successful, as attacks often missed their targets either due to operational failure or limited intelligence on the location of critical targets. In our concluding section we show that many of the conditions that were conducive to past success are not present in the contemporary Iran case. Overall, our findings reveal an interesting paradox. The historical cases that have successfully delayed proliferation are those when the attacking state struck well before a nuclear threat was imminent. Yet, this also happens to be when strikes are the least legitimate under international law, meaning that attacking under these conditions is most likely to elicit international censure.     

Optimizing search with positive information feedback

A search model is formulated in which positive information may be obtained, through the detection of trails, as to the target's earlier whereabouts. The corresponding Bayesian update formulas for target location probabilities are derived. The model does not appear to be amenable to rigorous optimization. A moving-horizon rule, and a heuristic simplification thereof, are, however, derived. In two numerical examples it is demonstrated that actively designing for detecting trail information, through use of these moving-horizon rules, has substantial potential advantage over using, for example, myopic rules even if the positive information is adaptively incorporated into location probabilities before applying the latter rules in each time period.     

防空导弹作战复杂电磁环境威胁势研究

为了分析和把握防空导弹作战面临的复杂电磁环境(CEME)态势,分析并建立了防空导弹作战CEME威胁模型;提出了防空导弹作战CEME威胁势概念,从态和势两方面深入分析了防空导弹作战CEME威胁势内涵,建立了防空导弹作战CEME威胁势函数模型;提出了基于集对分析(SPA)的防空导弹作战CEME威胁势评估新方法。论文研究对防空导弹作战电磁态势评估和电子对抗进程推演具有非常重要的理论指导意义和军事应用价值。     

Optimization of steerable sensor network for threat detection

A Markov chain approach to detecting a threat in a given surveillance zone by a network of steerable sensors is presented. The network has a finite number of predetermined states, and transition from one state to another follows a Markov chain. Under the assumption that the threat avoids detection, two game theoretic problems for finding an optimal Markov chain (two surveillance strategies) are formulated: the first maximizes the probability of threat detection for two consecutive detection periods, whereas the second minimizes the average time of detection for the worst‐case threat's trajectory. Both problems are reduced to linear programming, and special techniques are suggested to solve them. For a dynamic environment with moving noise sources, the optimal Markov chain changes at each detection period, and the rate of convergence of the Markov chain to its stationary distribution is analyzed. Both surveillance strategies are tested in numerical experiments and compared one with another. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

基于四面体六棱长的三站测时差立体定位方法

针对在三站测时差立体定位中辐射源位置不能唯一确定的情形,提出一种简单易懂、计算方便、可操作性强的解析解方法,以解决求解双曲面方程组的繁琐问题。首先利用三站相互之间的距离、由量测时差值换算得到的两个距离差值,以及辐射源至主站的距离(设为变量r)总共6个参数,立足于已知6条边长判断能否构成四面体的理论,求得r的取值范围;然后在r的值域范围内任意给定某个具体值,加上已知三站的地理位置,通过解三元一次方程组的形式获得目标在三站所在平面内垂直投影的坐标(设为变量X_h),并计算出目标至垂直投影的距离(设为变量h);最后由X_h和h给出目标在地心地固直角坐标系下的坐标。     

基于广义回归神经网络的单位运营状况分类

单位的运营状况会直接影响股东和广大人民的利益,针对运营状况可以使用广义回归神经网络进行分类。由于广义回归神经网络中径向基函数的扩展参数Spread的选取会导致分类的准确率,提出了一种果蝇优化算法优化参数Spread的分类模型。充分利用了果蝇优化算法的寻优能力,将优化后的参数代入到广义回归神经网络中对单位的财务数据进行运营状况的分类。结果表明,与广义回归神经网络做比较,优化后的网络模型对数据的分类可以达到很高的准确率,在相关领域的分类上有非常大的实用性。     

基于BP神经网络的极移预报*

为了提高地球定向参数极移的预报精度,建立了一个极移数据预报模型。利用傅里叶分析研究插值基础序列的周期特性,验证了基础序列重采样的可行性,提取插值基础序列数据的趋势项,利用多输入-单输出BP神经网络建模预报不同跨度的残差序列,合并趋势项和残差序列得到最终的极移预报。预报结果表明,选取合适的插值基础序列得到的预报极移精度较高,此BP神经网络能够有效地应用于地球定向参数极移的预报。     

IMM-EKF的弹道导弹轨道实时动态预测

快速准确的导弹轨道预测是有效进行导弹防御的前提。提出一种基于IMM-EKF的弹道导弹轨道实时动态预测方法,对导弹发射点和落点分别进行动态预测研究。首先,构建不包含导弹先验信息的IMM-EKF弹道估计器;其次,定义一种模型概率累积因子,用于估计导弹的关机时刻及相应的运动状态;最后,基于导弹运动状态的实时估计,动态预测落点和发射点。仿真实验结果表明:该方法能实时动态预测导弹发射点和落点;发射点预测应利用主动段状态估计,而落点预测则在导弹自由段早期进行为宜。     

基于态势预测的无人机防相撞控制方法

针对无人机自主飞行过程中,受空中非协作移动目标威胁较大,且空中移动威胁存在高机动性的特点,提出一种预测移动威胁情况下的无人机防撞控制方法,该方法采用交互多模(IMM)算法预测移动威胁的运动状态,同时利用滚动时域控制(RHC)思想建立无人机运动控制模型,构造有约束目标函数,运用微分进化算法(DE)求解目标函数,获取最优控制量,输入控制模型,完成防撞机动控制。仿真结果表明,该方法可以有效解决空中多架航空器同时入侵的防撞问题。     

基于BP神经网络的空中目标威胁排序

研究了BP神经网络算法对空中目标进行威胁排序的方法.水面舰艇对空防御作战中,舰载平台多传感器系统获得空中目标属性信息不完全,利用BP神经网络建立目标各属性权值的分配模型,通过大量的实例对模型进行训练,可以使所获得的空中目标属性信息得到充分利用,从而得到基本符合战场环境的客观的空中目标威胁排序.     

基于数字地形分析的智能兵力部署

兵力部署是指挥员组织实施战斗的重要工作,也是实现战斗决心的重要条件。在分析兵力部署原则基础上,结合兵种配置的地形条件和战术条件,提出了兵力部署适应度函数。采用遗传算法,设计了适应于数字地形分析的编码方案。实验证明,遗传算法能够有效解决兵力部署的智能化自动生成和评价问题,方法可行。     

On the brink: The resurgence of militant Islam in Central Asia

Since Operation Enduring Freedom, Central Asian militants, such as the Islamic Movement of Uzbekistan, have fled to Pakistan from their previous strongholds in Afghanistan. However, many militants have begun returning to Central Asia. Thus questions are raised as to what extent militancy has the potential to thrive with the pending North Atlantic Treaty Organization withdrawal from Afghanistan set for 2014? Is militancy a legitimate security threat to Central Asia? What strategies might militants implement? Thus, this article examines the current state of militancy, analyzes militant trends, introduces Afghanistan and Pakistan into the Central Asian equation, and determines the militants' capability and overall strategy. The article concludes that militant Islam, regardless of its current numbers, remains a viable threat to regional security, Afghanistan will be an essential factor for the future of Central Asian militancy, and the form this re-emergence will take becomes apparent.