复杂系统多属性决策方法

多属性决策已成为复杂系统评定的重要手段。属性标准化是多属性综合决策中的一项重要内容,标准化方法应严格遵循属性的物理意义和对决策目标的影响,要求标准化前后属性值比较的物理意义一致或接近。首先在分析现有标准化方法不足的基础上,提出了效益型、成本型和固定型属性标准化新方法,经过该方法得到的标准化结果,满足了标准化前后的可比性和线性化。其次,综合分析了加权和和加权积决策模型应用范围,得出加权积模型更适用于复杂系统的多属性综合决策问题研究。最后,将标准化方法和加权积决策模型应用于算例分析,分析结果验证了提出方法的有效性和一致性。     

一种多站无源联合定位系统的航迹起始方法

为了解决雷达系统面临的4大威胁,多站无源联合定位系统被广泛采用。航迹起始是多站无源联合定位系统对目标进行跟踪的首要问题。分析了多站无源联合定位系统的航迹起始问题的特点,在有源定位系统航迹起始的逻辑法基础上,利用辐射源参数构造多维相关波门进行关联判定,并采用基于最小二乘法的直线拟合方法对航迹作平滑处理,提出了一种针对多站无源联合定位系统的航迹起始方法。仿真实验结果表明了该算法的有效性。     

中程空空导弹可攻击区解算的新方法

建立空空导弹初始发射距离三维预估模型,提出一种空空导弹可攻击区解算的新算法。该算法将空空导弹初始发射距离预估模型与黄金分割法相结合,用导弹初始发射距离预估值构成黄金分割法的初始搜索区间,进行攻击区边界搜索。仿真结果表明,该算法提高了空空导弹可攻击区的精度,降低了边界搜索循环次数,具有有效性。     

曲面地表对远程火箭弹弹道影响的计算方法

远程火箭弹飞行时间长、射程远,必须考虑地球曲面地表对弹道的影响。分析了椭球地表模型下重力加速度的算法以及远程火箭弹射程的确定方法,根据远程火箭弹动力学模型,设计了一种以落点为原点的落点坐标系弹道仿真方法,比较了平面地表弹道模型、椭球地表弹道模型以及基于落点坐标系的曲面地表弹道模型的仿真效果。仿真结果表明,该方法不仅比椭球地表弹道模型简单而且精度很高,可以很好地解决曲面地表对弹道的影响。     

考虑降雨影响的飞机生存力模型与仿真分析

为研究更符合实际战场环境的飞机作战生存力,以降雨这一自然环境为典型,建立了雨杂波干扰下雷达对飞机的探测概率模型以及飞机生存力模型。认为飞机的RCS是Swerling起伏目标,通过确定综合信干比和最小可检测信噪比,采用蒙特卡罗法,利用MATLAB仿真了在雨杂波干扰和杂波抑制综合作用下飞机的生存力与距离的关系,并重点讨论了雷达波长和降雨状况对飞机生存力的影响。结论认为:在S波段内,降雨使飞机的生存力有一定程度的提高,且随着降雨量的增大和敌方雷达波长的减小,飞机生存力的提高更为明显;考虑降雨状况的影响,对于飞机生存力的研究是具有一定实际意义的。     

E级超级计算机故障预测的数据采集方法

面向未来E级超级计算机,提出用于故障预测的数据采集框架,能够全面采集与计算结点故障相关的状态数据。采用自适应多层分组数据汇集方法,有效解决随着系统规模增长数据汇集过程开销过大的问题。在TH-1A超级计算机上的实现和测试表明,该数据采集框架具有开销小、扩展性好的优点,能够满足未来大规模系统故障预测数据采集的需求。     

动态滑翔运动建模、机理分析与航迹优化

信天翁凭借动态滑翔的飞行技巧从梯度风中获取能量,从而在几乎不拍翅膀的情况下进行长时间、长距离飞行,这种技巧应用于小型无人机上可拓展其完成任务的能力。基于飞行器动力学对梯度风场中的无人机运动方程进行推导和简化处理;利用简化的运动方程,分别从非惯性参考系中的动能定理和机械能变化的角度,对动态滑翔获取能量的机理进行分析;利用微分平坦法,以最小平均控制输入变化率为目标函数,对徘徊模式和平移模式的动态滑翔航迹进行优化计算。分析结果表明:逆风爬升、顺风下滑是动态滑翔基本获能方式。优化结果表明:控制输入变得更加平滑,甚至出现阶段性的常值,使得控制更加简化;徘徊模式下,当风梯度作为决策变量时,优化过程可在[0,0.5 s-1]的区间上找到使得目标函数值最小的风梯度;平移模式下,目标函数值在该区间上单调递减。     

英语专业精读教学方法探讨

本文从精读教学普遍存在的几个问题出发，初步分析其产生的主要原因，并根据教学实践经验，探讨了精读教学改进方法，提出在精读课堂上，应采用多元化教学方法，以学生为教学活动的中心，采取语篇教学，重视精读泛读相结合，从而全面提高学生语言综合运用能力。     

A partial characterization of the optimal ordering/rationing policy for a periodic review system with two demand classes and backordering

We consider a finite horizon periodic review, single product inventory system with a fixed setup cost and two stochastic demand classes that differ in their backordering costs. In each period, one must decide whether and how much to order, and how much demand of the lower class should be satisfied. We show that the optimal ordering policy can be characterized as a state dependent (s,S) policy, and the rationing structure is partially obtained based on the subconvexity of the cost function. We then propose a simple heuristic rationing policy, which is easy to implement and close to optimal for intensive numerical examples. We further study the case when the first demand class is deterministic and must be satisfied immediately. We show the optimality of the state dependent (s,S) ordering policy, and obtain additional rationing structural properties. Based on these properties, the optimal ordering and rationing policy for any state can be generated by finding the optimal policy of only a finite set of states, and for each state in this set, the optimal policy is obtained simply by choosing a policy from at most two alternatives. An efficient algorithm is then proposed. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

An integer decomposition algorithm for solving a two‐stage facility location problem with second‐stage activation costs

We study a stochastic scenario‐based facility location problem arising in situations when facilities must first be located, then activated in a particular scenario before they can be used to satisfy scenario demands. Unlike typical facility location problems, fixed charges arise in the initial location of the facilities, and then in the activation of located facilities. The first‐stage variables in our problem are the traditional binary facility‐location variables, whereas the second‐stage variables involve a mix of binary facility‐activation variables and continuous flow variables. Benders decomposition is not applicable for these problems due to the presence of the second‐stage integer activation variables. Instead, we derive cutting planes tailored to the problem under investigation from recourse solution data. These cutting planes are derived by solving a series of specialized shortest path problems based on a modified residual graph from the recourse solution, and are tighter than the general cuts established by Laporte and Louveaux for two‐stage binary programming problems. We demonstrate the computational efficacy of our approach on a variety of randomly generated test problems. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010