Sequential learning versus no learning in Bayesian regression models

We consider two regression models: linear and logistic. The dependent variable is observed periodically and in each period a Bayesian formulation is used to generate updated forecasts of the dependent variable as new data is observed. One would expect that including new data in the Bayesian updates results in improved forecasts over not including the new data. Our findings indicate that this is not always true. We show there exists a subset of the independent variable space that we call the “region of no learning.” If the independent variable values for a given period in the future are in this region, then the forecast does not change with any new data. Moreover, if the independent variable values are in a neighborhood of the region of no learning, then there may be little benefit to wait for the new data and update the forecast. We propose a statistical approach to characterize this neighborhood which we call the “region of little learning.” Our results provide insights into the trade‐offs that exist in situations when the decision maker has an incentive to make an early decision based on an early forecast versus waiting to make a later decision based on an updated forecast. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 532–548, 2014     

The sixteenth-century antecedents of special operations ‘small war’

The first conceptual, theoretical treatises about small war (la petite guerre) as special operations appeared only from the middle of the seventeenth century. The term is not used in the eighteenth-century sense of ‘special operations’ in older sources. The supposed absence of any treatment of the subject is surprising considering the obsession with the ‘art of war’ in the Renaissance, but other authors attribute it to a supposed antinomy between chivalric ideals and irregular warfare. But the absence of explicit manuals on the subject is not evidence of absence of advanced reflection on this kind of operations in the Middle Ages and in Early Modern times. We should thus look elsewhere, in other genres, for writings that contain and pass on military knowledge. Epics, romances, educational and military treatises, and memoirs in fact contain elements of a theory of special operations, even though these genres differ from our conception of rationality inherited from the Enlightenment.     

Guerrillas and bandits in the Serranía de Ronda, 1810–1812

The Spanish Guerrilla (1808–1812) which has given its name to ideologically motivated insurgencies is usually portrayed as a patriotic uprising against the French occupation forces of Napoleon. It was that, in part, but also many other things besides. This case study illustrates its overlap and convergence with banditry but also with social unrest turned into uprisings directed by poor Spaniards against their creditors, as in the storming of Ronda by insurgents in 1810. From the propaganda of the day to the subsequent Spanish patriotic historiography, there has been a tendency to exaggerate the amplitude of events and also the damage that was done to the French forces and the casualty figures inflicted on them.     

面向空间应用的时间触发以太网

将时间触发协议增加到采用星型拓扑结构的以太网业务上,且保持完全兼容IEEE802.3标准,可解决空间有效载荷使用标准以太网通信遇到的实时性、确定性和可靠性问题。时间触发以太网基于全局基准时间,实时数据传输遵循严格的时序,支持时间和事件触发的两种通信过程。时间触发通道适合同步或周期性实时消息的传输,而事件触发通道适用于偶发或非周期性消息的传输。设计了空间应用以太网的拓扑结构和协议栈,介绍了系统通信的过程,进行了时间触发协议的研究,并对同步性能和网络性能进行了仿真验证。该以太网在保证可靠性、安全性的同时,增强了网络的灵活性,提高了网络利用率。     

航天侦察任务的关联度分析与去冗余方法

针对航天侦察需求响应中可能存在的任务重复产生问题,综合考虑任务的需求来源、质量要求、时间偏好及空间范围,提出一种基于任务关联度的任务冗余分析方法。对航天侦察的相关要素进行分析度量,给出了基于4类要素的任务关联度计算方法,提出了通过任务之间的关联度来降低可替代任务产生概率的具体算法,考虑了准确优先、公平优先以及混合等不同情况下的冗余度计算方法,给出一个应用示例,说明所述分析方法的有效性。研究结果表明,该方法具有良好的通用性,可为航天侦察任务的预处理提供有效支持。     

弹药库防静电方法研究

根据弹药库静电危险场所的分类等级,以形成静电危害的3个基本条件为依据,讨论了弹药库防静电危害常用措施:设施设备静电接地、防静电工作台、人体静电防护、铺设导电(或防静电)地面以及各自防静电要求.这些措施为防止和消除弹药库的静电危害提供了根本保障.     

美国2014年《四年防务评估报告》特点

2014年3月4日,美国国防部向国会提交了2014年版《四年防务评估报告》和《2015财年国防预算报告》。《四年防务评估报告》更新了再平衡战略,为美军建设提出了优先发展方向,要求美军联合部队向“更小型化”转型,以满足未来军事行动需求。     

一类具有饱和发生率的离散型SIS传染病模型

研究一类具有饱和发生率的离散型SIS传染病模型,得到了模型的基本再生数.通过线性化的方法,运用LaSalle-Lyapunov定理,证明当基本再生数R01时,无病平衡点是全局渐近稳定的;通过迭代的方法,证明当基本再生数R01时,地方病平衡点是全局渐近稳定的.     

基于重构相空间AD-SVM的短期电力负荷预测

利用重庆市九龙坡区电网2009年7月1日000-10月8日4：00 99 d共2 380个历史电力负荷数据,分析其特点和规律.将构建混沌理论的平均位移（AD）法和支持向量机（SVM）相结合,提出了一种新的短期电力负荷预测模型.通过仿真计算,将结果与神经网络法预测结果进行对比,可得新方法能较好反应数据变化趋势,并且具备较好的拟合能力,能够提高负荷预测精度.在实际短期电力负荷预测中,可优先选用平均位移法与支持向量机相结合的新方法.