Some recent findings in bayesian attribute single and double sampling

This article deals with several items, including theoretical and applied results. Specific topics include (1) a discrete, economically based, attributes acceptance sampling model and its adaptations, (2) relevant costs, (3) relevant prior distributions, (4) comparison of single- and double-sampling results, and (5) reasons for marginal implementation success following excellent implementation efforts. The basic model used is one developed by Guthrie and Johns; adaptations include provisions for fixed costs as well as modifications to permit double sampling. Optimization is exact, rather than approximate. Costs incorporated into the model are for sampling inspection, lot acceptance, and lot rejection. For each of these three categories a fixed cost is included as well as two variable costs, one for each item and the other for each defective item. Discrete prior distributions for the number of defectives in a lot are used exclusively. These include the mixed binomial and Polya distributions. Single- and double-sampling results are compared. Double sampling regularly performs at only slightly lower cost per lot than single sampling. Also, some cost and prior distribution sensitivity results are presented. Comments are provided regarding actual implementation experiences in industry. Practical deficiencies with the Bayesian approach are described, and a recommendation for future research is offered.     

多处理机系统中的宏任务并行

多处理机系统是巨型机的发展方向。宏任务是在多处理机系统上用来加快程序执行的一条主要途径。文中介绍了宏任务并行,描述了宏任务的实现,讨论了编译器和操作系统的支持。最后解释了宏任务的一个程序。     

样条函数康特诺维奇法在复合材料板和圆柱曲板弯曲及线性稳定性分析中的应用

样条函数康特诺维奇法是作者首先提出的一种结构数值计算方法。它实质上是一种离散形式的康特诺维奇法,将二维问题化为一维问题,使问题的自由度数大幅度减少。在本文中,基于Mindlin假设,将样条函数康特诺维奇法应用于金属、复合材料单层板及圆柱曲板的弯曲及线性稳定性分析。     

模糊逻辑在计算机医疗诊断中的应用

本文详细介绍了一医疗诊断专家系统的知识库组成,并提出了一种近似推理方法。知识库由模糊关系矩阵和推理规则集所组成。近似推理则是通过将推理规则模糊化来实现,它很好地解决了系统中存在的非精确性问题。     

二维非定常中子输运的并行算法

编制了求解时间相关二维中子输运问题的并行计算程序,并在YH-1计算机上进行过许多验证计算。对六个临界装置的计算表明,临界参数的计算值与实验值之间的偏差在参数值的实验误差范围之内,这证明计算程序是正确的。不同并行算法的计算结果完全相同也证实了程序编制的正确性。计算表明,并行程序的计算效率比相同参数下的串行程序提高约30倍以上。为了尽可能提高并行计算的效率,除了采取通常的向量化技巧外,在算法上提出了并维技巧和斜对角扫描的方法。     

A forward network simplex algorithm for solving multiperiod network flow problems

An optimization model which is frequently used to assist decision makers in the areas of resource scheduling, planning, and distribution is the minimum cost multiperiod network flow problem. This model describes network structure decision-making problems over time. Such problems arise in the areas of production/distribution systems, economic planning, communication systems, material handling systems, traffic systems, railway systems, building evacuation systems, energy systems, as well as in many others. Although existing network solution techniques are efficient, there are still limitations to the size of problems that can be solved. To date, only a few researchers have taken the multiperiod structure into consideration in devising efficient solution methods. Standard network codes are usually used because of their availability and perceived efficiency. In this paper we discuss the development, implementation, and computational testing of a new technique, the forward network simplex method, for solving linear, minimum cost, multiperiod network flow problems. The forward network simplex method is a forward algorithm which exploits the natural decomposition of multiperiod network problems by limiting its pivoting activity. A forward algorithm is an approach to solving dynamic problems by solving successively longer finite subproblems, terminating when a stopping rule can be invoked or a decision horizon found. Such procedures are available for a large number of special structure models. Here we describe the specialization of the forward simplex method of Aronson, Morton, and Thompson to solving multiperiod network network flow problems. Computational results indicate that both the solution time and pivot count are linear in the number of periods. For standard network optimization codes, which do not exploit the multiperiod structure, the pivot count is linear in the number of periods; however, the solution time is quadratic.     

微型计算机在测速雷达中的应用

利用测速雷达对各类弹头产生的信号进行处理以达到精确快速地测速之目的,这是目前世界上各靶场的基本测速手段。当前我国的测速雷达在信号处理方面突出问题是功能不全、可靠性差、实时性差和没有把计算机应用到测速雷达之中。针对这些问题,我们对我国靶场的部分测速雷达利用现成的微机进行了更新改装。本文就是反映如何利用微机把雷达信号进行数据处理达到高速和精确测速的目的。     

进化计算在机器人轨迹规划中的应用研究

本文介绍了采用进化计算思想研制的机器人轨迹规划系统ＲＴＰ－１，提出多层次动态结构化编码方案，利用低中高三层进化算法分别优化距离、路径和关节角度偏差，基于多层综合优化策略解决多目标多约束工程优化问题，建立了次序相关问题求解的通用框架。在进化算法中，利用拉马克效应加快轨迹规划速度，在ＲＭ－５０１机械手上实现的任意空间直线和空间曲线轨迹规划具有良好的鲁棒性，规划轨迹的相邻臂构型间具有良好的柔顺性，规划轨迹的臂构型序列具有良好的平滑性。本文所采用的机器人轨迹规划方法具有通用性，可推广应用于各种动力学系统的研制。     

条带式合成孔径雷达数字聚束算法

与聚束工作模式的合成孔径雷达 (SAR)相比 ,条带式SAR能够在相同时间内对更大范围的区域进行微波成像。但是在分析条带式SAR图像时 ,往往需要着重分析某些局部热点区域 (ROI ,Region-Of-Interest) ,而ROI外散射体的回波会降低ROI图像的对比度。本文的数字聚束 (Digitally -Spotlight)算法可以在成像前将ROI外的回波“过滤” ,实现等效的的聚束工作模式 ,从而提高SAR对比度。仿真验证了该算法的有效性。     

支持多媒体应用的CPU调度模型

多媒体应用的出现对操作系统调度模型提出了新的要求，许多多媒体系统中既有硬、软实时应用程序，又有传统的分时应用程序，希望在同一操作系统框架内得到支持。本文提出了支持上述功能的ＣＰＵ调度模型，并设计了两种算法来实现该模型：基于ＱｏＳ的ＣＰＵ带宽划分算法和双优先级调度算法。