定期维护与事后修理组合的维修策略

为了客观合理地制定产品的定期维护与事后修理组合的维修策略,分析了该组合策略下产品的性能变化特点,并从失效机理出发,利用复合Poisson过程描述了产品性能退化规律,建立了以产品长期运行下费用率最低为目标的优化模型,并通过求解得到了最优的维护周期.最后,实例分析表明:该方法能够较好地描述产品的性能退化规律;同时,优化得到的维修策略值可以有效地降低维修费用,并延长产品使用寿命.     

Unemployed youth: ‘time bombs’ or engines for growth?

While popular narratives about success in South Africa focus on individual effort, accidents of birth continue to determine life prospects. Inequalities in early childhood development, health, and education narrow the range of possibilities that young people have available to them, and this impacts on their risk appetite, including, through the workings of the maturing brain, a propensity to violence, substance abuse, and unsafe sex. New technology offers young people an unprecedented ability to organise and network. This fact, combined with high levels of youth dissatisfaction, unemployment, and marginalisation, leads many to worry that the young are “ticking time bombs”. While there certainly are risks, great unused pools of youth labour also present an opportunity for engaging them in social advancement programmes. Structured youth service is a tried and tested policy option that, when implemented as part of an integrated youth development strategy, can enlist thousands of young people in devoting their considerable energies to leadership for the public good.     

军事通信领域上下文本体建模及不确定性推理＊

为支持军事通信业务的智能化,研究了军事通信业务上下文信息的表示和推理,提出了一种表示业务上下文信息的语法结构、语义以及上下文元信息的本体建模方法。并利用贝叶斯网络理论,提出了一种支持不确定性推理的业务上下文认知模型的构建方法,最后通过案例分析验证了模型和结论的合理性。     

面向服务的作战仿真模型组合建模方法

为简化模型组合的实现方式,满足多样化作战仿真对模型服务组合的需求,针对作战仿真模型组合规则复杂、基本服务类型相对单一等特点,提出一种基于事件的服务组合BEWSC（Based-Events Web Services Composition）方法。首先定义一种基于MERA(mission-event-restriction-action)规则化语言,在此基础上,采用过程构造子,按照模块化方法对模型服务的组合方案进行描述,并分别从服务的发布者、服务的请求者和推理过程这三个角度对组合服务的执行流程进行具体分析,解决了服务组合表示困难、描述能力不足、模型匹配差异性大和模型组合有效性低等方面问题。     

基于群决策协同网络信息的掩护机编队选择

针对任务机群中掩护机编队的选择,用群决策协同网络信息模型进行了掩护机编队的选择。首先,给出了协同网络、模糊数和语言变量的相关概念;其次,分析了掩护机编队选择的指标体系框架和协同网络信息框架;然后,构建了群决策协同网络信息的数学模型,在此基础上,给出了方案选择的步骤;最后,运用该模型对掩护机编队的选择进行求解。结果表明：该模型能够综合群体专家的知识,解决掩护机编队选择中的定性判断问题。该模型可用于个体指标和协同指标均为定性指标时的方案优选问题。     

地球静止轨道高能电子通量在线预测模型研究

利用粒子群优化算法和最小二乘支持向量机，建立了地球静止轨道高能电子通量(1.8-3.5MeV)在线预测模型。针对粒子群优化算法，提出了一种新的粒子群多样性测度计算方法，有效改善了其早熟收敛现象；基于改进的粒子群优化算法优化最小二乘支持向量机的正则化参数和核参数；利用滑动时间窗口策略更新模型数据，设计变量选择触发机制以及模型的再学习机制实现模型的在线预测功能。[根据题目的调整，对摘要做了相应改动]通过对2000年电子通量监测数据和相关太阳风、地磁参数等实际数据进行提前1-3天的预测实验，表明了所建在线预测模型具有较高的预测性能，有一定的实用价值。     

基于熵权的岸基油料保障设施设备效能评估

岸基油料保障是舰艇油料保障的重要方式，岸基油料保障设施设备效能直接影响舰艇油料保障效率。通过对影响岸基油料保障设施设备效能因素的分析，从储油设施设备、输油设施设备、油料装卸加注设施设备3个方面建立了评价指标体系。针对评价中指标权重确定时主观性较强的缺点，引入信息熵的概念进行评价指标权重的计算，建立了基于熵权的岸基油料保障设施设备效能评估模型。通过对3个基地岸基油料保障设施设备效能的实例分析，验证了模型，为舰艇岸基油料保障提供了决策依据。     

Information theory for ranking and selection

We study the classical ranking and selection problem, where the ultimate goal is to find the unknown best alternative in terms of the probability of correct selection or expected opportunity cost. However, this paper adopts an alternative sampling approach to achieve this goal, where sampling decisions are made with the objective of maximizing information about the unknown best alternative, or equivalently, minimizing its Shannon entropy. This adaptive learning is formulated via a Bayesian stochastic dynamic programming problem, by which several properties of the learning problem are presented, including the monotonicity of the optimal value function in an information-seeking setting. Since the state space of the stochastic dynamic program is unbounded in the Gaussian setting, a one-step look-ahead approach is used to develop a policy. The proposed policy seeks to maximize the one-step information gain about the unknown best alternative, and therefore, it is called information gradient (IG). It is also proved that the IG policy is consistent, that is, as the sampling budget grows to infinity, the IG policy finds the true best alternative almost surely. Later, a computationally efficient estimate of the proposed policy, called approximated information gradient (AIG), is introduced and in the numerical experiments its performance is tested against recent benchmarks alongside several sensitivity analyses. Results show that AIG performs competitively against other algorithms from the literature.     

基于模糊聚类方法的机场目标选择模型

在现代战争中,机场作为一个战略级别的目标,要发挥其整体的作用需要目标群中的每个子目标都能最大限度地相互配合,使其本身的价值充分地体现出来.针对当前在目标选择上片面的问题,根据模糊聚类方法的基本原理,结合机场本身的特征进行改进,构建了机场目标选择模型,通过计算,证明可以克服以往目标打击方案界定的不明确性,避免了选择目标的单一化.     

面向基本对象模型BOM和Web服务的建模技术研究

介绍了BOM模型和面向Web服务技术，从概念、表示以及语义层次上对2种技术进行了对比分析。基于二者数据类型和语义的一致性，提出了从BOM模型到Web服务描述的映射规则，阐述了这种映射的实际操作步骤，最后通过实例验证了该方法的可行性和有效性，并分析和总结了运用BOM和Web服务建模的优越性。