线性相依风险下的超额赔款再保险

本文从保险人的角度研究对两类相依风险的超额赔款再保险的最优自留额问题。考虑指数效用函数的货币期望效用原则和自留累积损失的调节系数原则,得到关于这两个问题的最优解的方程。     

The effects of model parameter deviations on the variance of a linearly filtered time series

We consider a general linear filtering operation on an autoregressive moving average (ARMA) time series. The variance of the filter output, which is an important quantity in many applications, is not known with certainty because it depends on the true ARMA parameters. We derive an expression for the sensitivity (i.e., the partial derivative) of the output variance with respect to deviations in the model parameters. The results provide insight into the robustness of many common statistical methods that are based on linear filtering and also yield approximate confidence intervals for the output variance. We discuss applications to time series forecasting, statistical process control, and automatic feedback control of industrial processes. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

Analytic solution for the nucleolus of a three‐player cooperative game

The nucleolus solution for cooperative games in characteristic function form is usually computed numerically by solving a sequence of linear programing (LP) problems, or by solving a single, but very large‐scale, LP problem. This article proposes an algebraic method to compute the nucleolus solution analytically (i.e., in closed‐form) for a three‐player cooperative game in characteristic function form. We first consider cooperative games with empty core and derive a formula to compute the nucleolus solution. Next, we examine cooperative games with nonempty core and calculate the nucleolus solution analytically for five possible cases arising from the relationship among the value functions of different coalitions. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

Approximation results for min‐max path cover problems in vehicle routing

This article studies a min‐max path cover problem, which is to determine a set of paths for k capacitated vehicles to service all the customers in a given weighted graph so that the largest path cost is minimized. The problem has wide applications in vehicle routing, especially when the minimization of the latest service completion time is a critical performance measure. We have analyzed four typical variants of this problem, where the vehicles have either unlimited or limited capacities, and they start from either a given depot or any depot of a given depot set. We have developed approximation algorithms for these four variants, which achieve approximation ratios of max{3 ‐ 2/k,2}, 5, max{5 ‐ 2/k,4}, and 7, respectively. We have also analyzed the approximation hardness of these variants by showing that, unless P = NP , it is impossible for them to achieve approximation ratios less than 4/3, 3/2, 3/2, and 2, respectively. We have further extended the techniques and results developed for this problem to other min‐max vehicle routing problems.© 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

基于前景理论的CGF Agent决策建模研究

前景理论(Prospect Theory,PT)描述了个体在不确定条件下的决策规律,较好地刻画了决策者的风险偏好。分析表明,PT在作战决策建模中具有一定的适用性和可行性。提出了一种基于PT的计算机生成兵力(Computer Generated Forces,CGF)Agent决策建模方法,给出了CGF Agent的建模框架,对CGF Agent决策过程中方案选择的具体步骤和算法进行了详细阐述。实验表明,所提出的方法在一定程度上提高了CGF Agent决策行为的真实性,证明了所提出方法的有效性。     

基于复杂网络的作战网络分析

分布式网络化作战是网络中心战的基础,而分布式作战网络的构建是网络化作战的重要前提。首先,运用复杂网络的相关参数分析了多种不同的网络,选择了BA非标度网络作为分布式作战网络的最优表现形式;其次,以BA非标度网络为基础提出了一个适合军事上动态鲁棒性分析的模型DCNCE;最后,仿真结果表明,在以网络效能值为测度的对比下,分布式作战网络在介数毁伤策略下更脆弱,为构建并改进现有的作战网络提供了理论依据。     

基于模糊-组合神经网络的信息系统安全风险评估

针对信息系统的安全风险评估问题,提出了一种将模糊理论与神经网络进行"浅层次"结合的评估方法。通过对信息系统所涉及的风险因素分别从资产影响、威胁频度、脆弱性严重程度三方面进行分析,建立了信息系统的安全风险层次化结构,并构造了各因素所对应评判集的隶属度矩阵;综合运用模糊推理算法与神经网络仿真技术,对信息系统的安全风险进行评估,进而判定信息系统安全风险等级。最后,通过实例分析说明了算法的应用,并借助误差分析检测了模型的有效性。     

RBF神经网络在深V型滑行艇阻力预报中的应用

基于SV、JYK系列滑行艇的阻力、浸湿面积、航行纵倾角试验数据,采用RBF神经网络建立了深V型滑行艇阻力预报数值图谱;针对艇艉底部横向斜升角变化的有限试验数据,提出了一种基于小样本试验数据的阻力修正方法。试验表明,该方法对深V型滑行艇(折角线长度与最大折角线宽度比在4~5.5,面积负荷系数在5.5~7,重心纵向相对位置在3%~9%,艉部艇底斜升角在5°~25°之间变化)阻力预报是可行的。在相同精度下,针对该文研究的问题,RBF神经网络所需时间少于BP神经网络。     

基于层间嵌入式多级支持向量机的特征选择

针对多故障样本一次性映射之后分类不理想,研究了多级层次式支持向量机,应用UCI数据仿真,结果表明该方法缩短了训练时间、提升了测试准确率、改善了样本的可分类性。由于误差积累,在此基础上,提出了层间嵌入式多级支持向量机,采用Abalone数据仿真,结果表明分类精度有所提高并减少了分类步骤。结合ReliefF算法,对制导设备的故障特征参数进行了选择。     

基于CAS/Agent的装甲装备战损模型仿真

针对传统战损模型研究方法存在的不足,提出用人工神经网络的学习能力模拟Agent的适应性。借鉴CAS(Complex Adaptive System)理论的建模思想,引入ERA(Environment-Rules-Agents)方案建立战损模型。在外部干预Agent作用下,运用BP算法并结合CT(Cross Target)算法对红蓝双方对抗战斗进行仿真,模拟动态战场环境下装备损伤的演化过程。该模型可更好地理解装备损伤的动力学特性。