非线性奇异摄动系统的反馈线性化

研究了一类非线性奇异摄动系统的反馈线性化问题。首先,利用积分流形的概念,建立了原系统关于小参数的N阶近似系统,然后,讨论了N阶近似系统的线性化,导出了线性化变换的计算公式,并举例说明了方法的应用。     

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。     

基于反馈线性化的飞行器姿态运动的变结构控制方法研究

利用反馈线性化方法对飞行器姿态运动的非线性耦合进行了解耦,并对得到的线性化系统进行了变结构姿态控制系统设计,该控制系统具有优良的控制品质和鲁棒性。数字仿真结果进一步证实该方法的有效性。     

The effects of model parameter deviations on the variance of a linearly filtered time series

We consider a general linear filtering operation on an autoregressive moving average (ARMA) time series. The variance of the filter output, which is an important quantity in many applications, is not known with certainty because it depends on the true ARMA parameters. We derive an expression for the sensitivity (i.e., the partial derivative) of the output variance with respect to deviations in the model parameters. The results provide insight into the robustness of many common statistical methods that are based on linear filtering and also yield approximate confidence intervals for the output variance. We discuss applications to time series forecasting, statistical process control, and automatic feedback control of industrial processes. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

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.     

非线性联轴器动态特性的理论分析

对钢丝绳联轴器的动态特性进行理论分析,并运用谐波平衡法研究非线性弹性联轴器激励响应的动态特征．提出建立动刚度数学模型的方法以及阻尼的处理方法．     

导弹大攻角高机动飞行特性分析与仿真

以新一代无翼式气动布局导弹为背景,在大攻角气动特性理论基础上,分析了在导弹主动段、攻角在180°范围内变化的导弹飞行特性,得出了90°内大攻角最大转弯能力和180°攻角附近最大降速效果的结论。进行了俯仰平面S型轨迹机动飞行仿真,仿真结果说明了大攻角飞行的高机动特性。     

DESIGNING A VIABLE PREDICTION MARKET TO FORECAST DEFENSE ACQUISITION COST AND SCHEDULE OUTCOMES

This paper is the first to demonstrate a viable prediction market that successfully forecasts defense acquisition cost and schedule outcomes, and to provide insights for defense executive decision‐making. Already used in private industry, prediction markets can also accurately forecast outcomes and their associated risks for government programs. Using virtual money, prediction markets allow traders to ‘bet’ on some future outcome. This market mechanism turns out to be a relatively simple and accurate way to discover, aggregate, and communicate to a defense executive the collective market’s beliefs about the likelihood of an eventual outcome of an acquisition program of interest.