基于ICP的编队预定目标选择方法

如何对编队预定目标进行自动选择,是超视反舰导弹亟待解决的一个问题.反舰末制导雷达对编队预定目标的选择,可通过点集匹配来实现,基于此提出了一种运用ICP (Iterated Closest Point)算法进行编队预定目标选择的方法.首先通过一个粗搜索过程来确保ICP算法的初始值选取性能,然后运用ICP算法精确搜索最佳匹...     

基于蚂蚁聚类算法的炮兵阵地选取方法

在对炮兵作战地域进行地形分析的基础上,提出运用蚂蚁聚类算法选取炮兵阵地的方法.针对炮兵阵地配置的特殊要求,将模糊数学中的隶属度概念引入到炮兵阵地聚类算法之中.最后通过实验分析了此方法的优缺点,对炮兵指挥决策有一定的参考价值.     

基于免疫FNN算法的加热炉炉温优化控制

针对复杂钢坯加热过程,提出了一种免疫克隆进化模糊神经网络(ICE-FNN)控制算法。首先根据现场样本数据建立过程神经网络模型;然后基于该模型,采用模糊神经网络控制器(FNNC)规则优化算法,确定FNNC的最佳规则数;最后由FNNC的规则优化所得参数构造初始种群的一个解,采用免疫克隆进化(ICE)算法对FNNC参数优化。该算法具有全局寻优和局部求精能力,仿真结果证实了其有效性。     

Better is the Neighbor?

Abstract

This study applies the Sequential Panel Selection Method (SPSM), to investigate the convergence properties of the military expenditure of the North Atlantic Treaty Organization (NATO) during the period of 1990–2015. Compared to the traditional methods, SPSM considers fundamentally general spatial homogeneous and heterogeneous relationships with countries and examines the evolution of military expenditure. We find that four-fifths of NATO member countries have been convergent with the UK, but no country’s military expenditure is convergent with the US. This means that there is no significant linkage effect in the US for NATO military expenditure. While they are allies of the US, the majority of NATO member countries’ military expenditures are consistent with UK military expenditure. The main reasons are due to the geographical space layout and the international relationship convergence. The results indicate that more than four-fifths of NATO member countries have been coordinated with convergence theory and spillover effect.     

一种基于层次分析法的舰炮武器系统选型综合评价模型

针对舰炮武器系统选型配置决策中众多制约因素难以平衡兼顾的难题,本文基于层次分析法,综合了作战效能、全寿命周期费用、研制周期、适装性、技术可行性和发展潜力等多变量因素,提出并建立了一套综合优化舰炮武器系统选型配置方案的方法和模型,实现了舰炮武器系统选型配置问题的优化决策,最后以大口径主炮武器系统发展选型为例,给出了模型的应用实例。     

基于结构加权的海面编队预定目标选择方法

海面目标运动和编队阵型的约束特性,使得通过对装订阵型和末制导探测阵型进行点集匹配来选择预定目标成为一种有效途径。但当编队目标释放干扰时,会引起阵型结构发生局部变化,导致目标选择性能恶化。本文基于反舰导弹目标选择需求,分析了传感器导航和探测误差、装订信息误差、编队目标运动和释放干扰等因素所引起的位置点集变形,通过利用阵型中未污染的结构信息,提出了基于几何散列法和结构加权平均Hausdorff距离的编队预定目标选择方法。理论分析和实验结果表明,该方法不受传感器导航误差和编队目标整体运动的影响,在编队存在冲淡干扰时能有效提高目标选择能力。     

目标选择理论方法

针对现代战争特点和要求,给出了适合不同目标系统的6种打击目标选择理论,即重心效应理论、链条效应理论、瓶颈效应理论、连累效应理论、层次效应理论和组合理论。并运用这些理论,针对不同类型目标,给出了6种方法,即非线性规划方法、集合论方法、矩阵方法、群落型方法、网络型方法和塔型方法,基本涵盖了远程攻击武器目标选择理论与方法。     

Estimating the probability that a simulated system will be the best

Consider a stochastic simulation experiment consisting of v independent vector replications consisting of an observation from each of k independent systems. Typical system comparisons are based on mean (long‐run) performance. However, the probability that a system will actually be the best is sometimes more relevant, and can provide a very different perspective than the systems' means. Empirically, we select one system as the best performer (i.e., it wins) on each replication. Each system has an unknown constant probability of winning on any replication and the numbers of wins for the individual systems follow a multinomial distribution. Procedures exist for selecting the system with the largest probability of being the best. This paper addresses the companion problem of estimating the probability that each system will be the best. The maximum likelihood estimators (MLEs) of the multinomial cell probabilities for a set of v vector replications across k systems are well known. We use these same v vector replications to form v^k unique vectors (termed pseudo‐replications) that contain one observation from each system and develop estimators based on AVC (All Vector Comparisons). In other words, we compare every observation from each system with every combination of observations from the remaining systems and note the best performer in each pseudo‐replication. AVC provides lower variance estimators of the probability that each system will be the best than the MLEs. We also derive confidence intervals for the AVC point estimators, present a portion of an extensive empirical evaluation and provide a realistic example. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 341–358, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10019     

适用于捷联惯性/星光组合导航的导航星表构建方法

构建满足完备性、精简性和查询快速性的导航星表是实现捷联惯性/星光组合导航系统的重要前提和保证。为了达到这一目标，本文选取天文学中的Tycho-2星表作为导航星表的初始星表，它与TRC星表相比具有明显的优势，在实践运用过程中更加完备。在Tycho-2星表基础上，对球矩形分区方法进行了改进，包括明确了分区及子分区的划分方法，提出了备选导航星的选择策略。实验结果表明，采用改进型球矩形分区方法的备选导航星数量最多只占赤纬带法导航星的19.39%，仅占全天遍历法导航星的3.12%。因此，改进型球矩形分区方法更加精准，查询更快捷，更适用于SINS/CNS组合导航系统。     

目标选择的一个优化模型

坦克作战过程中 ,经常出现一个坦克群遭遇对方一个坦克群的情况 ,这时每辆坦克往往向威胁自身最大的目标开火 ,但这种选择的整体效果不一定最优。本文提出一种目标选择方法 ,使得最大限度地减轻了对方对己方的威胁 ,大大提高了作战坦克对敌杀伤效果