基于信息论的C3I系统决策性能的评价

信息熵是描述信息系统的一种比较成功的方法.采用信息论的方法对决策系统进行描述,在考虑了决策者的有界合理性限制和达到满意性能指标的要求下,分析了单人指挥决策系统的系统性能,并在此基础上分析了多人指挥决策系统的系统性能,最后得出采用决策系统的误差概率P和相互一致性度量Q作为评价C3I系统决策性能标准的结论.     

分布式防空C3I系统面向对象建模方法

采用面向对象的建模思想,把分布式防空C3I系统的各个组成部分抽象成对象,从时间、空间和功能的角度对分布式防空C3I系统进行了描述.通过确定对象类、类的属性、操作及类之间的关系而建立了分布式防空C3I系统的对象模型;通过对系统状态转换的分析,建立了分布式防空C3I系统动态模型;通过对系统功能模型的分布,利用层次数据流图建立了分布式防空C3I系统功能模型.     

基于遗传算法的目标方位角估算

针对某型武装直升机加装微光电视瞄准系统后 ,提出了采用遗传算法进行微光电视图像的识别和提取 ,然后与模型基元进行图像匹配 ,来研究目标方位角的估算问题。经分析计算 ,能较好地满足需求 ,为微光电视瞄准原理的实现打下一定的基础。     

关于《机械设计工程》教学体系的研究与实践

论述了机械设计系列课程体系改革的必要性,分析了国内外机械设计系列课程的教学体系,重点介绍了机械设计系列课程新的教学体系的内容,并规划了教改实践的方法和步骤.     

Generating Pareto‐optimal boundary points in multiparty negotiations using constraint proposal method

In this paper a constraint proposal method is developed for computing Pareto‐optimal solutions in multiparty negotiations over continuous issues. Constraint proposal methods have been previously studied in a case where the decision set is unconstrained. Here we extend the method to situations with a constrained decision set. In the method the computation of the Pareto‐optimal solutions is decentralized so that the DMs do not have to know each others' value functions. During the procedure they have to indicate their optimal solutions on different sets of linear constraints. When the optimal solutions coincide, the common optimum is a candidate for a Pareto‐optimal point. The constraint proposal method can be used to generate either one Pareto‐optimal solution dominating the status quo solution or several Pareto‐optimal solutions. In latter case a distributive negotiation among the efficient points can be carried out afterwards. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 210–225, 2001     

后方油库整体生存概率分析计算

针对我军后方油库特点,探讨了油库整体生存概率计算的基本思路和方法,分析了各类分项目标生存概率的计算方法,采用层次分析对后方油库各分项目标权值进行了详细分析计算,可为后方油库伪装防护效能评估提供依据。     

HLA在C3I系统仿真中的应用

首先介绍了C3I系统仿真的特点,以及高层系统结构HLA的思想,并对其在C3I系统仿真中的应用作了初步的讨论     

Effectiveness of (R,Q) policies in one‐warehouse multiretailer systems with deterministic demand and backlogging

Consider a distribution system with a central warehouse and multiple retailers. Customer demand arrives at each of the retailers continuously at a constant rate. The retailers replenish their inventories from the warehouse which in turn orders from an outside supplier with unlimited stock. There are economies of scale in replenishing the inventories at both the warehouse and the retail level. Stockouts at the retailers are backlogged. The system incurs holding and backorder costs. The objective is to minimize the long‐run average total cost in the system. This paper studies the cost effectiveness of (R, Q) policies in the above system. Under an (R, Q) policy, each facility orders a fixed quantity Q from its supplier every time its inventory position reaches a reorder point R. It is shown that (R, Q) policies are at least 76% effective. Numerical examples are provided to further illustrate the cost effectiveness of (R, Q) policies. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 422–439, 2000     

机载激光雷达数据的三维深度学习树种分类

针对传统基于激光雷达(Light Detection And Ranging,LiDAR)数据的树种分类方法难以直接且全面地利用点云的三维结构信息的问题,提出一种基于三维深度学习的机载LiDAR数据的树种分类方法.该方法直接从三维数据中抽象出高维特征,而无须将点云转化为体素或二维图像.以塞罕坝国家森林公园内白桦和落叶松...     

Optimal policies for M/M/m queue with two different kinds of (N,T)‐policies

In this paper, two different kinds of (N, T)‐policies for an M/M/m queueing system are studied. The system operates only intermittently and is shut down when no customers are present any more. A fixed setup cost of K > 0 is incurred each time the system is reopened. Also, a holding cost of h > 0 per unit time is incurred for each customer present. The two (N, T)‐policies studied for this queueing system with cost structures are as follows: (1) The system is reactivated as soon as N customers are present or the waiting time of the leading customer reaches a predefined time T, and (2) the system is reactivated as soon as N customers are present or the time units after the end of the last busy period reaches a predefined time T. The equations satisfied by the optimal policy (N*, T*) for minimizing the long‐run average cost per unit time in both cases are obtained. Particularly, we obtain the explicit optimal joint policy (N*, T*) and optimal objective value for the case of a single server, the explicit optimal policy N* and optimal objective value for the case of multiple servers when only predefined customers number N is measured, and the explicit optimal policy T* and optimal objective value for the case of multiple servers when only predefined time units T is measured, respectively. These results partly extend (1) the classic N or T policy to a more practical (N, T)‐policy and (2) the conclusions obtained for single server system to a system consisting of m (m ≥ 1) servers. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 240–258, 2000