广义Liénard方程Poincaré分岔极限环的唯一性和不存在性

讨论了一类广义Linard方程x¨+f1(x)x.2+εf2(x)x.+g(x)=0的Poincar分岔极限环的唯一性和不存在性。将不对Abel积分进行分项,而是利用一阶Mel′nikov函数直接从整体上进行分析讨论,得出了若干判别准则和充分条件。     

Production planning with resources subject to congestion

A fundamental difficulty in developing effective production planning models has been accurately reflecting the nonlinear dependency between workload and lead times. We develop a mathematical programming model for production planning in multiproduct, single stage systems that captures the nonlinear dependency between workload and lead times. We then use outer linearization of this nonlinear model to obtain a linear programming formulation and extend it to multistage systems. Extensive computational experiments validate the approach and compare its results to conventional models that assume workload‐independent planning lead times. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

模糊理论与D-S理论在指控系统目标识别融合中的应用

多传感器信息融合技术已获得了普遍的关注和广泛的应用,其理论和方法已成为智能信息处理的一个重要领域,模糊理论与证据理论(D-S)是主要的技术之一.在某试飞指控系统中,为了获得可靠的识别结果需要目标识别的融合问题.系统的从实际出发提出了基于模糊理论与D-S理论的目标识别融合方法.仿真计算结果表明,该模型和方法具有方法简单、运算量小和识别结果可靠等优点,具有一定的理论意义和使用价值.     

基于Stateflow的复杂可修系统的建模与仿真方法

介绍了应用Stateflow对复杂可修系统进行建模与仿真的方法.首先,对复杂可修系统与Stateflow相关概念进行了简单介绍.然后,利用有限状态机理论与面向对象编程思想提出了建立基于Stateflow复杂可修系统模型的思路、分析步骤、难点问题的解决以及参数统计模型;最后,使用Stateflow对一类复杂可修系统进行了具体的建模与仿真.仿真结果表明,基于Stateflow的模型与仿真能够有效地评估复杂可修系统的可靠性参数特征,并具有可视化、流程化和层次化的特点.     

舰船空调系统不同保障模式的效费分析

分析了舰船全寿命期和使用期的结构,在此基础上,借助于WSEIAC模型,分别对舰船空调系统在两种保障方式的全寿命使用期效能和费用的各个指标进行了建模,提出了指标计算的思路与计算方法.结合海军舰船特点,在对WSEIAC效能模型进行修改和完善的基础上,给出了计算示例,结果显示了海军舰船空调系统采用岸基保障方式的合理性和优越性.     

Nonpreemptive scheduling of independent tasks with prespecified processor allocations

In this article we study the problem of scheduling independent tasks, each of which requires the simultaneous availability of a set of prespecified processors, with the objective of minimizing the maximum completion time. We propose a graph-theoretical approach and identify a class of polynomial instances, corresponding to comparability graphs. We show that the scheduling problem is polynomially equivalent to the problem of extending a graph to a comparability graph whose maximum weighted clique has minimum weight. Using this formulation we show that in some cases it is possible to decompose the problem according to the canonical decomposition of the graph. Finally, a general solution procedure is given that includes a branch-and-bound algorithm for the solution of subproblems which can be neither decomposed nor solved in polynomial time. Some examples and computational results are presented. © 1994 John Wiley & Sons, Inc.     

目标位置不确定性的图形描述

目标的观测和状态估计涉及目标的各种运动和属性数据,其中位置不确定性是最重要的性能指标.借鉴测绘学科中衡量点元位置不确定性的方法,分别用椭圆和椭球来表示二维目标和三维目标的位置误差散布的不确定性区域.从位置误差的协方差矩阵导出1-σ误差椭圆(球)参数,再由椭圆(球)的概率分布导出相应的95%圆(球)概率误差的半径.位置不确定性的图形描述为评价位置观测数据的质量提供了可视化的方法.     

Bayesian inference for a Lanchester type combat model

We undertake inference for a stochastic form of the Lanchester combat model. In particular, given battle data, we assess the type of battle that occurred and whether or not it makes any difference to the number of casualties if an army is attacking or defending. Our approach is Bayesian and we use modern computational techniques to fit the model. We illustrate our method using data from the Ardennes campaign. We compare our results with previous analyses of these data by Bracken and Fricker. Our conclusions are somewhat different to those of Bracken. Where he suggests that a linear law is appropriate, we show that the logarithmic or linear‐logarithmic laws fit better. We note however that the basic Lanchester modeling assumptions do not hold for the Ardennes data. Using Fricker's modified data, we show that although his “super‐logarithmic” law fits best, the linear, linear‐logarithmic, and logarithmic laws cannot be ruled out. We suggest that Bayesian methods can be used to make inference for battles in progress. We point out a number of advantages: Prior information from experts or previous battles can be incorporated; predictions of future casualties are easily made; more complex models can be analysed using stochastic simulation techniques. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 541–558, 2000     

基于深度学习的战役初始态势认知方法

战役初始态势不仅影响着整个战役进程,而且对战役筹划的影响也极为显著。以深度学习为代表的人工智能技术突飞猛进,为我们利用人工智能技术实现自动识别复杂的战役初始态势、模拟战役指挥员的经验知识带来了契机,作者就此问题进行初步探索性研究。对战役初始态势的概念及其类型进行了介绍,探讨了基于深度学习的战役初始态势认知模型构建,对模型构建步骤、输入和输出的设计进行了探讨,对卷积神经网络的基本思想、结构、训练进行了介绍,在示例中介绍了样本数据的录入程序、卷积神经网络的具体结构与应用程序,验证了方法的可行性与有效性。所提出的战役初始态势认知方法可以在一定程度上获得指挥员对战役初始态势的经验知识。     

Exploiting self‐canceling demand point aggregation error for some planar rectilinear median location problems

When solving location problems in practice it is quite common to aggregate demand points into centroids. Solving a location problem with aggregated demand data is computationally easier, but the aggregation process introduces error. We develop theory and algorithms for certain types of centroid aggregations for rectilinear 1‐median problems. The objective is to construct an aggregation that minimizes the maximum aggregation error. We focus on row‐column aggregations, and make use of aggregation results for 1‐median problems on the line to do aggregation for 1‐median problems in the plane. The aggregations developed for the 1‐median problem are then used to construct approximate n‐median problems. We test the theory computationally on n‐median problems (n ≥ 1) using both randomly generated, as well as real, data. Every error measure we consider can be well approximated by some power function in the number of aggregate demand points. Each such function exhibits decreasing returns to scale. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 614–637, 2003.