过程挖掘算法

过程挖掘又称工作流挖掘,主要依据日志中记录的过程实例执行信息重构工作流过程模型,是工作流再设计与分析方法的一项关键技术。对目前主流的过程挖掘算法和相关工具进行了研究,把过程挖掘算法按照特性及解决问题分成了4类,对每类算法的优缺点进行比较研究。最后指出了目前过程挖掘研究中存在的问题。     

作战信息需求模型

研究了作战信息需求的概念、需求分析流程及描述方法,提出了作战信息需求的概念模型、逻辑模型和过程模型。概念模型界定了作战信息需求的相关概念及层次关系;逻辑模型描述了作战信息需求的内容;过程模型分析了作战信息需求的演化过程。     

小子样条件下巡航导弹的命中精度评估方法

针对巡航导弹定型试验发数少、验前试验信息源多的特点,提出小子样条件下,通过可信性检验分别得到每个验前信息源的可信度,在导弹落点偏差分布为正态-逆伽马分布的假设下,获得评估的验前分布参数,选择基于可信度的加权方法对多源验前信息进行融合,采用Bayes估计方法得到命中精度。最后结合实例进行仿真,说明了该方法较传统的Bayes方法更稳健,很适合巡航导弹命中精度的评估。     

贝叶斯网络推理在信息系统安全风险评估中的应用

提出了一种基于贝叶斯网络推理的安全风险评估方法。从实际出发建立信息系统的贝叶斯网络模型,根据专家给出的先验信息,结合获得的证据信息,运用Pearl方法完成对模型的评估,给出在特定条件下模型的计算——线性推理算法。最后,以实例分析信息系统安全评估的实现过程,结果表明,该方法可行、有效。     

面向对象的虚拟维修性分析中零件信息建模方法研究

采用面向对象建模的方法,在研究维修活动的基础上,利用逆向思维,将维修活动中的维修对象即零部件作为维修活动的主体,借用计算机语言中类的定义方式,将零部件的各种数据定义为类的相应属性值,将零部件在维修活动的被动行为定义为零件类的动作函数,将维修作业中维修动作的人为判断变成基于零件属性的自动判断,并给出了基于这种建模方式的虚拟环境中自动维修仿真作业的实现过程。结果表明,虚拟维修中需要人力判断的工作大大减少,缩短了虚拟维修仿真的时间,从而可以提高系统的仿真效率。     

基于层次分析法的化工企业火灾风险评估研究

化工企业火灾风险评估对于化工生产至关重要。针对化工行业的火灾风险,结合层次分析法和模糊识别模式的优点,提出了基于层次分析—模糊识别的综合评价方法,并通过实例评估证明了这种评价方法行之有效。     

论终身教育趋势下军校教师学习的终身化

学习,是人类认识自然和社会、不断完善和发展自我的必由之路。终身学习是21世纪的生存概念,是教师自身发展和适应职业的必由之路。教师专业发展是一个随时代变迁永无止境的过程。在终身教育趋势下,军校教师要不断提高自己,树立终身学习观念。     

Modeling and analysis of a mixed‐model assembly line with stochastic operation times

We consider a mixed‐model assembly line (MMAL) comprised a set of workstations and a conveyor. The workstations are arranged in a serial configuration. The conveyor moves at a constant speed along the workstations. Initial units belonging to different models are successively fed onto the conveyor, and they are moved by the conveyor to pass through the workstations to gradually generate final products. All assembling tasks are manually performed with operation times to be stochastic. An important performance measure of MMALs is overload times that refer to uncompleted operations for operators within their work zones. This paper establishes a method to analyze the expected overload times for MMALs with stochastic operation times. The operation processes of operators form discrete time nonhomogeneous Markov processes with continuous state spaces. For a given daily production schedule, the expected overload times involve in analyzing the Markov processes for finite horizon. Based on some important properties of the performance measure, we propose an efficient approach for calculating the expected overload times. Numerical computations show that the results are very satisfactory. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Combining standardized time series area and Cramér–von Mises variance estimators

We propose three related estimators for the variance parameter arising from a steady‐state simulation process. All are based on combinations of standardized‐time‐series area and Cramér–von Mises (CvM) estimators. The first is a straightforward linear combination of the area and CvM estimators; the second resembles a Durbin–Watson statistic; and the third is related to a jackknifed version of the first. The main derivations yield analytical expressions for the bias and variance of the new estimators. These results show that the new estimators often perform better than the pure area, pure CvM, and benchmark nonoverlapping and overlapping batch means estimators, especially in terms of variance and mean squared error. We also give exact and Monte Carlo examples illustrating our findings.© 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Estimation of average backorders for an assemble‐to‐order system with random batch demands through extreme statistics

We investigate inventory management for a large‐scale multi‐product, multi‐component Assemble‐to‐Order system with general random batch demands. Results from extreme statistics theory are applied in developing approximation schemes for a widely used performance measure, customer backorders. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007