基于累积前景理论的时间矩阵多属性综合评判模型

针对动态多属性方案排序优选决策问题,提出了一种基于累积前景理论的时间矩阵序列动态多属性综合评判系统模型。依据累积前景理论,将时间矩阵序列动态多属性决策转化为关于属性期望的益损时间矩阵序列动态决策,综合考虑各属性权重、各时间点的权重,计算各方案的最终综合前景值,并依据其大小对方案进行综合评判排序。最后给出了一个决策实例。     

基于边界相切拟合的轴对称工件缺陷重构方法

针对轴对称工件超声检测缺陷重构问题,通过分析传统基于传播时间反演方法的不足和误差产生的原因,提出了一种基于边界相切拟合的缺陷重构方法,并针对实际检测缺陷的类型,采用圆和椭圆作为模型对缺陷进行重构。从重构结果上看,当检测实心体工件时,圆形缺陷的圆拟合重构误差不大于0.1 mm,圆形缺陷的椭圆拟合重构误差小于0.4 mm,椭圆形缺陷的椭圆拟合重构误差小于0.3 mm,空心体工件由于检测方式不同,误差会比实心体大一些。     

金属弹簧脱碳层厚度与受热温度和时间的关系

应用给定温度下保温和模拟典型火灾温度曲线两种受热方式 ,对成品 6 5Mn弹簧进行受热处理 ,测定在不同受热温度与时间下弹簧的脱碳层厚度 ,发现在受热温度超过 6 0 0℃以后 ,随着受热时间和温度的增加 ,脱碳层厚度也随之增加。认为运用被火灾作用的弹簧钢脱碳层厚度可以鉴定火场中不同部位的受热温度和时间。     

DSP实现低信噪比条件下点目标检测与跟踪

针对嵌入式实时图像处理系统中 ,复杂背景低信噪比条件下红外运动点目标检测及跟踪所采用的处理算法 ,包括基于空域低通滤波的多图像平均法和自适应阈值分割法以及基于目标运动时空连续性目标运动轨迹拟合及目标运动轨迹参数预测算法 ,进行基于二维数组组合方式存储结构的算法复杂度估计 ,并将上述算法在TI公司的TMS32 0C6 2 0 1EVM板上进行实时性能评测 ,说明上述算法在基于具有软件流水性能的TMS32 0C6x系列DSP嵌入式实时图像处理系统中实现的可行性。     

弹炮结合武器系统效能评估

简要分析了发展近程反导武器系统的必要性和弹炮结合系统的优势,并以近程舰炮武器系统为基础,给出了弹炮结合系统的基本组成。利用WSEIAC模型及系统组成的串并联关系,分析了系统在开始工作时,以及在工作过程中,可能出现的不同状态,并建立了它的效能评估数学模型。最后根据实际工程应用经验数据,对弹炮结合系统的效能进行了计算,并分析了计算结果,为系统的设计、研制、评价提供了依据。     

ANSYS在方位保持部件温度场分析中的应用

在对方位保持部件进行合理简化的基础上,建立了方位保持部件的三维有限元模型.运用ANSYS5.6的热分析功能对温控过程中方位保持部件的工作环境进行了定量热分析,为测温点的设置提供了重要参考.     

Analysis of down times of jib cranes—A stochastic approach

In this paper a case study dealing with the maintenance problem of jib cranes is presented. A jib crane is viewed as a complex system whose performance is observed as a single realization over period of time. After pointing out limitations of existing stochastic models to analyze the observed realization a new family of bivariate stochastic processes is introduced. The data of jib crane is analyzed using new model and cross‐validated using part of the data set. It is noted that the new family of stochastic processes is useful to analyze bivariate data where one of the variables is finitely valued and the other is nonnegative and continuous. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 231–243, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10006     

Scheduling with variable time slot costs

In this article, we study a class of new scheduling models where time slot costs have to be taken into consideration. In such models, processing a job will incur certain cost which is determined by the time slots occupied by the job in a schedule. The models apply when operational costs vary over time. The objective of the scheduling models is to minimize the total time slot costs plus a traditional scheduling performance measure. We consider the following performance measures: total completion time, maximum lateness/tardiness, total weighted number of tardy jobs, and total tardiness. We prove the intractability of the models under general parameters and provide polynomial‐time algorithms for special cases with non‐increasing time slot costs.© 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

Adaptive random search for continuous simulation optimization

We present, analyze, and compare three random search methods for solving stochastic optimization problems with uncountable feasible regions. Our adaptive search with resampling (ASR) approach is a framework for designing provably convergent algorithms that are adaptive and may consequently involve local search. The deterministic and stochastic shrinking ball (DSB and SSB) approaches are also convergent, but they are based on pure random search with the only difference being the estimator of the optimal solution [the DSB method was originally proposed and analyzed by Baumert and Smith]. The three methods use different techniques to reduce the effects of noise in the estimated objective function values. Our ASR method achieves this goal through resampling of already sampled points, whereas the DSB and SSB approaches address it by averaging observations in balls that shrink with time. We present conditions under which the three methods are convergent, both in probability and almost surely, and provide a limited computational study aimed at comparing the methods. Although further investigation is needed, our numerical results suggest that the ASR approach is promising, especially for difficult problems where the probability of identifying good solutions using pure random search is small. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

基于两阶段感染过程分析的蠕虫传播模型SSI

合理的蠕虫传播模型可以准确地描述蠕虫类恶意代码在网络中的传播行为,有助于在开展蠕虫防护、检测和抑制技术的研究时更深入地分析蠕虫的传播机制。通过引入和分析蠕虫的感染时间这个在经典的传染病模型研究中被忽略的重要因素,使用确定性建模分析方法推导得出SSI蠕虫传播模型,合理地反映网络中的脆弱性主机在蠕虫传播时可能的状态转换。模拟仿真表明,SSI模型可以相对准确地描述蠕虫类恶意代码在网络中的传播过程。