防空C~3I系统战前辅助决策的MADM模型及框架设计

存在于Ｃ３Ｉ系统中的决策是大量且复杂的。首先详细分析了野战防空Ｃ３Ｉ系统战前决策的五个基本内容;然后,根据多属性决策（ＭＡＤＭ）理论,提出了一种统一的战前辅助决策的ＭＡＤＭ模型,并从实际出发,给出了求解随机的ＡＤＭ问题的三个适用方法;最后讨论了辅助决策系统的枢架设计及实现方法。     

基于神经网络的超精密机床伺服进给非线性模型辨识

以双轴Ｔ型结构的超精密金刚石车床的伺服进给系统为研究对象,采用自构造神经网络技术,建立了系统的非线性动态数学模型,为系统非线性控制与补偿提供参考模型     

基于损伤树及损伤征兆集的战场损伤定位研究

建立了基于损伤树的知识表示、知识推理模型及损伤树评估框架,利用损伤树各节点的损伤征兆集,进行装备战场损伤定位,较好地利用了装备专家的领域知识,提高了战场损伤评估的准确性和效率。     

《经济地理学》教学中研究性学习的探索

研究性学习是一种实践性较强的教育教学活动。文章阐述了研究性学习的内涵，明确了经济地理学课程教学中研究性学习的目标，归纳了经济地理学课程中研究性学习的内容，并提出了研究性学习的实施策略。     

论寓教于乐的教学理念与设计

“寓教于乐”是一种理想的教育教学目标，也是大学教学改革的重点，教育游戏的出现为教学拓宽了道路，实践着“寓教于乐”的理念。通过参阅大量文献资料，对教育游戏的概念与现状进行了阐述，并提出了教育游戏的设计理念与策略，为教育游戏的设计提供指导和帮助。     

THE CONCEPT OF NUCLEAR LEARNING

This article seeks to elucidate the concept of nuclear learning. It explores both the “nuclear” and the “learning” aspects of the concept. On the nuclear side, it distinguishes between learning basic facts about nuclear arms and drawing inferences about the larger implications of those facts. On the learning side, it discusses three issues: whether to use the term in a normative or value-neutral manner; the difference between learning that leads to a change in means versus learning that leads to a re-evaluation of ends; and whether learning only takes place at the level of individuals or whether there can also be learning by collective entities. The article argues there is no universal best answer to these questions and that the particular concept of learning that should be employed depends on the goals of the analyst. If the goal is to reduce the chances of nuclear war, however, one type of learning that will be important to consider is whether there is shared, cross-national learning.     

Learning in counterinsurgency: what do we really know?

Since the publication in 2002 of John Nagl's Learning to Eat Soup with a Knife, organizational learning has been widely presumed an important ingredient for success in counterinsurgency. But sampling the literature from before and after this time shows remarkably little analytical treatment of the issue of learning and even confusion over what it may mean. This article considers the theories, hypotheses, research strategies, threats to validity, methods of measurement, treatments of time, and general lack of statistical analysis in the work to date and recommends a course for future research.     

新疆石河子内初班学生的学习适应性研究

为深入了解内初班学生的学习适应性状况,本研究分别在石河子市四所内初班承办学校中,严格按照分层抽样的方法选取了294名学生作为被试,采用《学习适应性测验》量表探求内初班学生的学习适应性特征。结果显示:石河子内初班学生的学习适应性与全国常模基本一致,学习适应不良主要集中在学习技术和学习态度上。在性别上、年级上差异不显著,民考民和民考汉学生的学习适应性在全量表上差异显著,总体上民考民学生的学习适应性优于民考汉学生。     

利用深度学习的硬件计数器复用估计算法

利用深度学习方法,为硬件计数器复用(multiplexing,MPX)提供结果精度更高的估计模型。通过对MPX估计得到的结果与实际采集的真实数据进行相似性分析,证明相同程序多次运行之间得到的硬件计数值是线性相关的。采用神经网络多层感知器(multilayer perceptron,MLP)和双向门控神经网络(bidirectional gated recurrent unit, Bi-GRU)这2种深度学习模型,对MPX数据进行拟合。基于动态时间规整(dynamic time warping, DTW),提出一个全新的评估MPX数据精度的指标DTW-cost。实验结果表明,同时收集15个硬件事件数据时,MLP方法拟合得到的13个高性能计算应用平均准确率比现有使用最广的固定插值法高出10.53%,最多可提升19.8%;而在MLP表现较差的事件上,Bi-GRU方法得到的平均准确率提升了28.8%。     

Bayesian strategies for dynamic pricing in e‐commerce

E‐commerce platforms afford retailers unprecedented visibility into customer purchase behavior and provide an environment in which prices can be updated quickly and cheaply in response to changing market conditions. This study investigates dynamic pricing strategies for maximizing revenue in an Internet retail channel by actively learning customers' demand response to price. A general methodology is proposed for dynamically pricing information goods, as well as other nonperishable products for which inventory levels are not an essential consideration in pricing. A Bayesian model of demand uncertainty involving the Dirichlet distribution or a mixture of such distributions as a prior captures a wide range of beliefs about customer demand. We provide both analytic formulas and efficient approximation methods for updating these prior distributions after sales data have been observed. We then investigate several strategies for sequential pricing based on index functions that consider both the potential revenue and the information value of selecting prices. These strategies require a manageable amount of computation, are robust to many types of prior misspecification, and yield high revenues compared to static pricing and passive learning approaches. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007