黑体辐射数值反演新方法

应用广义偏离原则对黑体辐射问题进行了反演的研究,给出了正则参数的选择方法,由计算机仿真结果知,该方法计算精度高,有良好的应用前景。     

Heuristics for the multi‐resource generalized assignment problem

The well‐known generalized assignment problem (GAP) involves the identification of a minimum‐cost assignment of tasks to agents when each agent is constrained by a resource in limited supply. The multi‐resource generalized assignment problem (MRGAP) is the generalization of the GAP in which there are a number of different potentially constraining resources associated with each agent. This paper explores heuristic procedures for the MRGAP. We first define a three‐phase heuristic which seeks to construct a feasible solution to MRGAP and then systematically attempts to improve the solution. We then propose a modification of the heuristic for the MRGAP defined previously by Gavish and Pirkul. The third procedure is a hybrid heuristic that combines the first two heuristics, thus capturing their relative strengths. We discuss extensive computational experience with the heuristics. The hybrid procedure is seen to be extremely effective in solving MRGAPs, generating feasible solutions to more than 99% of the test problems and consistently producing near‐optimal solutions. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 468–483, 2001     

Bayesian inference based on partial monitoring of components with applications to preventive system maintenance

Consider a binary, monotone system of n components. The assessment of the parameter vector, θ, of the joint distribution of the lifetimes of the components and hence of the reliability of the system is often difficult due to scarcity of data. It is therefore important to make use of all information in an efficient way. For instance, prior knowledge is often of importance and can indeed conveniently be incorporated by the Bayesian approach. It may also be important to continuously extract information from a system currently in operation. This may be useful both for decisions concerning the system in operation as well as for decisions improving the components or changing the design of similar new systems. As in Meilijson [12], life‐monitoring of some components and conditional life‐monitoring of some others is considered. In addition to data arising from this monitoring scheme, so‐called autopsy data are observed, if not censored. The probabilistic structure underlying this kind of data is described, and basic likelihood formulae are arrived at. A thorough discussion of an important aspect of this probabilistic structure, the inspection strategy, is given. Based on a version of this strategy a procedure for preventive system maintenance is developed and a detailed application to a network system presented. All the way a Bayesian approach to estimation of θ is applied. For the special case where components are conditionally independent given θ with exponentially distributed lifetimes it is shown that the weighted sum of products of generalized gamma distributions, as introduced in Gåsemyr and Natvig [7], is the conjugate prior for θ. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 551–577, 2001.     

A risk function for the stochastic modeling of electric capacity expansion

We present a stochastic optimization model for planning capacity expansion under capacity deterioration and demand uncertainty. The paper focuses on the electric sector, although the methodology can be used in other applications. The goals of the model are deciding which energy types must be installed, and when. Another goal is providing an initial generation plan for short periods of the planning horizon that might be adequately modified in real time assuming penalties in the operation cost. Uncertainty is modeled under the assumption that the demand is a random vector. The cost of the risk associated with decisions that may need some tuning in the future is included in the objective function. The proposed scheme to solve the nonlinear stochastic optimization model is Generalized Benders' decomposition. We also exploit the Benders' subproblem structure to solve it efficiently. Computational results for moderate‐size problems are presented along with comparison to a general‐purpose nonlinear optimization package. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48:662–683, 2001     

Convolutions and generalization of logconcavity: Implications and applications

Additive convolution of unimodal and α‐unimodal random variables are known as an old classic problem which has attracted the attention of many authors in theory and applied fields. Another type of convolution, called multiplicative convolution, is rather younger. In this article, we first focus on this newer concept and obtain several useful results in which the most important ones is that if is logconcave then so are and for some suitable increasing functions ?. This result contains and as two more important special cases. Furthermore, one table including more applied distributions comparing logconcavity of f(x) and and two comprehensive implications charts are provided. Then, these fundamental results are applied to aging properties, existence of moments and several kinds of ordered random variables. Multiplicative strong unimodality in the discrete case is also introduced and its properties are investigated. In the second part of the article, some refinements are made for additive convolutions. A remaining open problem is completed and a conjecture concerning convolution of discrete α‐unimodal distributions is settled. Then, we shall show that an existing result regarding convolution of symmetric discrete unimodal distributions is not correct and an easy alternative proof is presented. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 109–123, 2016     

基于子阵结构的相控阵MIMO雷达分辨能力分析

在阵元总数一定的情况下,不同的子阵划分方式和布阵间距对不同子阵发射正交波形,子阵内发射相干波形的相控阵-MIMO雷达系统的分辨力的影响,首先通过相控阵-MIMO雷达的信号模型推导出其广义模糊函数,然后以此分析子阵结构对距离、多普勒、方位三维分辨力的影响。仿真结果表明,在阵元总数一定的情况下,子阵越多,系统距离分辨力越高,子阵越大,多普勒分辨力越高,子阵间距满足一定条件才能有较好的系统分辨力。这些结论对相控阵-MIMO雷达子阵结构设计具有指导意义。     

基于通用扩张状态观测器的鲁棒飞行控制方法

针对参数不确定、外界干扰与测量噪声情况下飞行控制问题,提出一种基于通用扩张状态观测器的鲁棒飞行控制方法。基于状态相关的Riccati方程控制方法对飞行器俯仰通道非线性模型进行扩展线性化;引入基于通用扩张状态观测器的控制方法,设计干扰补偿增益,实现对外界干扰的估计与补偿;通过在线解算状态相关矩阵及代数黎卡提方程,得出状态反馈增益与干扰补偿增益,实现对飞行器期望攻角的跟踪控制。与已有方法对比表明,所提方法不仅对系统模型不确定性与外界干扰具有较强的鲁棒性,而且在较大测量噪声情况下,其依然能够保证良好的跟踪控制效果,具有较强的工程应用价值。     

基于两级隐式形状模型的抗遮挡目标跟踪

为解决遮挡条件下的目标跟踪问题,提高定位精度,提出一种基于两级隐式形状模型的目标跟踪算法。首先利用Fast Hessian检测子提取待跟踪目标及周围区域的局部关键点区域构建码本字典,用SURF描述子获取码本的特征描述矢量建立码本支持模型,然后利用广义Hough变换建立码本字典集与目标之间的共生关系,通过隐式形状模型进行在线学习更新,最后通过寻找投票空间中的极大值来对目标进行定位,根据跟踪过程中目标遮挡程度的不同,分别赋予目标自身码本投票及周围码本投票不同权重,提高不同遮挡状态下目标定位精度。实验结果表明,在目标被遮挡甚至不可见或者丢失后重新回到视场时,该算法均能鲁棒地定位出目标。     

基于转移费用矩阵的机器人路径规划方法

本文描述了机器人路径规划的一种新方法：基于转移费用矩阵的机器人路径规划方法。通过定义转移费用矩阵的概念及其上的二元运算,将最优路径的生成,转化为矩阵的运算,使得有限步的矩阵运算,即可得到环境中所有点间的最优路径,达到了在预处理阶段构造最优路径集的目的。最后,介绍了该方法在移动机器人任务规划中的应用     

时间距离像消隐时弹头进动与结构参数估计

考虑弹道目标时间距离像存在消隐现象,提出了一种弹道目标微距离变化曲线断续时进动与结构参数提取方法。首先,建立了弹道中段目标宽带回波模型,推导了散射中心微距离变化曲线理论公式;其次,提取了时间距离像中各散射中心的微距离变化曲线,据此提出采用选点方法实现目标进动频率和平动参数联合估计,完成了弹道目标时间距离像的平动补偿;最后,利用扩展Hough变换方法进行补偿后断续微距离变化曲线的检测,基于各散射中心间的相对位置信息实现了弹道目标的结构参数提取。电磁仿真实验验证了该方法的有效性。