基于灰色系统理论的火灾事故预测方法

简要叙述应用灰色系统理论进行火灾事故预测的理论和方法 ,建立了火灾事故预测的GM (1,1)模型 ,并用该模型对火灾事故进行预测。     

维修方式再探讨

本文根据近几年关于维修方式讨论中提出的一些问题,在维修方式的分类、应用决策、设计要求和效能等方面,联系维修实际进行了探讨,提出了一些原则、方法和观点。     

C4ISR系统需求工程中作战过程描述方法

对于建设C4ISR系统来说,系统需求工程的出发点之一应该是基于对作战的描述.同时对目前作战过程进行描述的若干方法进行分析对比,结合实际情况对作战过程描述进行讨论并给出新的切入点,最后给出一个简单的描述示例.     

基于UML的侦察监视系统仿真分析

侦察监视系统的仿真是一体化联合作战仿真系统的重要组成部分。根据侦察监视系统的未来发展,进行了侦察监视系统的仿真需求分析,提出了仿真系统所要实现的基本功能,并利用UML对侦察监视仿真系统的角色、用例进行了分析,用用例图对整个仿真系统功能进行了描述。在此基础上,对系统进行了静态建模和动态建模。结果表明利用UML对侦察监视系统进行仿真分析,过程完整、易于理解,便于获取军事需求。     

后勤物资消耗测算系统设计需求分析

针对当前后勤物资消耗测算方法过于简单粗略的问题,以构建有效的后勤物资消耗测算系统为目的,对系统的设计进行了需求分析。介绍了后勤物资消耗测算的基本流程以及关键理论,研究了后勤物资消耗测算系统的用户特点以及应用流程,着重对系统的功能需求进行了分析,确定了系统各主要功能的相关内容,并按照功能需求确定了系统的组成结构和接口关系,为系统的设计和实现奠定了基础。     

基于WBS的装备作战需求联合论证任务流程设计方法

针对装备作战需求联合论证中任务分解与协同困难的问题,以构建融合业务活动与管理活动的集成论证活动为目标,提出了基于WBS的装备作战需求论证活动分解方法,分析了装备作战需求论证活动分解的原理、原则和活动表示方法,研究了业务活动与管理活动的WBS分解过程,研究了业务活动与管理活动的集成方法和协同分析方法,初步构建了基于WBS的装备作战需求联合论证任务流程模型,为进一步优化和调整装备作战需求论证流程、提高论证工作效率和成果质量提供了新的方法。     

基于油液分析的装备状态多阶段组合预测模型

状态预测是状态维修的关键步骤之一。针对装备状态变化规律复杂、特点难易准确掌握的关键问题,以延时时间概念和两阶段预知模型为基础,提出了根据不同阶段特点采用不同预测方法的多阶段组合预测模型。通过油液分析及其相关规定,对装备运行阶段进行了具体划分,给出了适应各阶段特点的预测方法。最后,通过实例验证了该模型的有效性。     

Minimum violations and predictive meta‐rankings for college football

This article presents two meta‐ranking models that minimize or nearly minimize violations of past game results while predicting future game winners as well as or better than leading current systems—a combination never before offered for college football. Key to both is the development and integration of a highly predictive ensemble probability model generated from the analysis of 36 existing college football ranking systems. This ensemble model is used to determine a target ranking that is used in two versions of a hierarchical multiobjective mixed binary integer linear program (MOMBILP). When compared to 75 other systems out‐of‐sample, one MOMBILP was the leading predictive system while getting within 0.64% of the retrodictive optimum; the other MOMBILP minimized violations while achieving a prediction total that was 2.55% lower than the best mark. For bowls, prediction sums were not statistically significantly different from the leading value, while achieving optimum or near‐optimum violation counts. This performance points to these models as potential means of reconciling the contrasting perspectives of predictiveness versus the matching of past performance when it comes to ranking fairness in college football. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 61: 17–33, 2014     

An adaptive forecasting algorithm and inventory policy for products with short life cycles

Products with short life cycles are becoming increasingly common in many industries, such as the personal computer (PC) and mobile phone industries. Traditional forecasting methods and inventory policies can be inappropriate for forecasting demand and managing inventory for a product with a short life cycle because they usually do not take into account the characteristics of the product life cycle. This can result in inaccurate forecasts, high inventory cost, and low service levels. Besides, many forecasting methods require a significant demand history, which is available only after the product has been sold for some time. In this paper, we present an adaptive forecasting algorithm with two characteristics. First, it uses structural knowledge on the product life cycle to model the demand. Second, it combines knowledge on the demand that is available prior to the launch of the product with actual demand data that become available after the introduction of the product to generate and update demand forecasts. Based on the forecasting algorithm, we develop an optimal inventory policy. Since the optimal inventory policy is computationally expensive, we propose three heuristics and show in a numerical study that one of the heuristics generates near‐optimal solutions. The evaluation of our approach is based on demand data from a leading PC manufacturer in the United States, where the forecasting algorithm has been implemented. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

基于体系结构的指挥信息系统需求论证方法

需求论证是指挥信息系统建设的重要环节。本文在DODAF2.0体系结构框架研究基础上,设计了指挥信息系统军事需求论证框架。主要探讨了能力需求、作战需求、服务需求、系统需求、采办需求和技术标准需求的论证过程。最后结合实例论述了指挥信息系统军事需求的分析方法及步骤,为指挥信息系统军事需求论证提供了指导。该研究在指挥信息系统需求工程领域具有一定的理论和现实指导意义。