Weibull tolerance intervals associated with moderate to small survival proportions for use in a new formulation of lanchester combat theory

Given herein is an easily implemented method for obtaining, from complete or censored data, approximate tolerance intervals associated with the upper tail of a Weibull distribution. These approximate intervals are based on point estimators that make essentially most efficient use of sample data. They agree extremely well with exact intervals (obtained by Monte Carlo simulation procedures) for sample sizes of about 10 or larger when specified survival proportions are sufficiently small. Ranges over which the error in the approximation is within 2 percent are determined. The motivation for investigation of the methodology for obtaining the approximate tolerance intervals was provided by the new formulation of Lanchester Combat Theory by Grubbs and Shuford [3], which suggests a Weibull assumption for time-to-incapacitation of key targets. With the procedures investigated herein, one can use (censored) data from battle simulations to obtain confidence intervals on battle times associated with given low survivor proportions of key targets belonging to either specified side in a future battle. It is also possible to calculate confidence intervals on a survival proportion of key targets corresponding to a given battle duration time.     

导弹遥测故障的GM-Verhulst-SCGM预测算法

遥测故障预测是保障导弹遥测系统可靠性的基础。根据导弹遥测故障的历史数据,结合GM(1,1)模型、Verhucst模型和SCGM(1,1)c模型构建了导弹遥测故障的GM-Verhulst-SCGM组合灰色预测模型,按照预测有效度算法取得组合预测模型的权重系数。选用导弹遥测故障的训练组实际值作为原始数据,分别利用各预测模型估算对比组导弹遥测故障数据。预测结果表明,相比单一预测模型,组合灰色预测模型具备更高的故障预测精度。在验证组合灰色预测模型可行性的基础上,进一步估算了同一型号导弹未来时序的遥测故障数据,为相关部门及时改善导弹遥测技术及避免导弹故障提供理论及方法借鉴。     

Properties of a source location estimator in the plane

The statistical properties of an estimator of a source location were established by simulation for the case in which the source location is estimated—using transformation of lines to points—from the angles in which different observers see the source, and both the assumed locations of the observer points and the observed angles are subject to error. It was found that for normal error distributions the estimator is unbiased, and the resulting estimates are approximately normally distributed with a small standard deviation. An easy-to-use and reliable forecasting formula was suggested to forecast the parameters of the distributions of the estimates for different observer-source relationships. © 1993 John Wiley & Sons, Inc.     

作战油料需求预计不确定性因素及误差分析

当前各种油料需求预计单纯地追求表面精确而忽视实有误差,重静止轻动态,脱离了作战保障实际。从技术、勤务和战术结合的层面,将油料需求预计不确定性因素归结为油料消耗标准本身、计划与实际运用差异、影响油耗的自然因素考虑不同、作战任务理解判断差别四点,并对各自的误差范围进行了粗略分析。提出的不确定性因素及误差范围界定,有助于引发人们对作战油料需求预计新的思考,提高油料勤务理论研究和实践能力水平。     

System comparison procedures for automatic target recognition systems

Estimating the performance of an automatic target recognition (ATR) system in terms of its probability of successfully identifying a target involves extensive image collection and processing, which can be very time‐consuming and expensive. Therefore, we investigate the Wald sequential test for the difference in two proportions as a sample size‐reducing alternative to ranking and selection procedures and confidence intervals. An analysis of the test parameters leads to a practical methodology for implementing the Wald test for fairly comparing two systems, based on specific experimental goals. The test is also extended with the modified, sequentially rejective Bonferroni procedure for the multiple pairwise comparison of more than two systems. Two sampling schemes for different experimental goals are also discussed. The test methodology is applied to actual data to compare different configurations of a specific ATR system, with the results demonstrating that the modified Wald sequential procedure is a useful alternative to comparing proportions with confidence intervals, particularly when data are expensive. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 357–371, 1999     

BP网络在火灾形势预测中的应用

分析将BP网络应用于火灾预测研究的可行性与优势 ,并将神经网络与时间序列分析相结合 ,对火灾形势预测进行探讨     

柴油机磨损寿命的灰色马尔柯夫模型预测

基于灰色系统理论,将灰色ＧＭ（１,１）预测模型和马尔柯夫预测模型的优点结合起来,形成一个灰色马尔柯夫预测模型,拓宽了灰色预测的应用范围。特别地,这种模型的预测结果比其它随机波动性较大的数据到模型的预测结果精确得多。对柴油机磨损寿命进行预测,取得了令人满意的结果。     

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     

A note on a comparison of confidence interval techniques in truncated life tests

Several approximate procedures are available in the literature for obtaining confidence intervals for the parameter A of an exponential distribution based on time truncated samples. This paper contains the results of an empirical study comparing three of these procedures.     

基于改进核极限学习机和集成学习理论的目标机动轨迹预测

为了提高目标轨迹预测的精度以及预测模型的泛化能力,提出基于改进蝙蝠算法优化的核极限学习机(Kernel Extreme Learning Machine,KELM)和集成学习理论目标机动轨迹预测模型。构建KELM模型,并采用改进的蝙蝠算法对KELM的参数进行优化;以优化后的KELM神经网络为弱预测器,结合集成学习算法生成强预测器,通过训练不断优化强预测的结构和参数,得到一种基于集成学习理论的目标机动轨迹预测模型;基于不同规模的样本,将所得预测模型与逆传播神经网络、支持向量机和极限学习机等模型进行对比分析。仿真结果表明:所提目标机动轨迹预测模型具有较好的预测精度和泛化能力。     

FORECASTING SERIES CONTAINING OFFSETTING BREAKS: OLD SCHOOL AND NEW SCHOOL METHODS OF FORECASTING TRANSNATIONAL TERRORISM

Transnational terrorism data are difficult to forecast because they contain an unknown number of structural breaks of unknown functional form. The rise of religious fundamentalism, the demise of the Soviet Union, and the rise of al Qaeda have changed the nature of transnational terrorism. ‘Old School’ forecasting methods simply smooth or difference the data. ‘New School’ methods use estimated break dates to control for regime shifts when forecasting. We compare the various forecasting methods using a Monte Carlo study with data containing different types of breaks. The study's results are used to forecast various types of transnational terrorist incidents.     

Statistical analysis of very high-dimensional data sets of hierarchically structured binary variables with missing data: An application to marine corps readiness evaluations

The present analysis deals with very high-dimensional data sets, each one containing close to 900 binary variables. Each data set corresponds to an evaluation of one complex system. These data sets are characterized by large portions of missing data where, moreover, the unobserved variables are not the same in different evaluations. Thus, the problems which confront the statistical analysis are those of multivariate binary data analysis, where the number of variables is much larger than the sample size and in which missing data varies with the sample elements. The variables, however, are hierarchically structured and the problem of clustering variables to groups does not exist in the present study. In order to motivate the statistical problem under consideration, the Marine Corps Combat Readiness Evaluation System (MCCRES) is described for infantry battalions and then used for exposition. The present article provides a statistical model for data from MCCRES and develops estimation and prediction procedures which utilize the dependence structure. The E-M algorithm is applied to obtain maximum-likelihood estimates of the parameters of interest. Numerical examples illustrate the proposed methods.     

基于改进GM(1,1)模型的导弹贮存可靠性预测方法

针对导弹系统技术复杂、贮存样本量受限、测试数据波动性较大等特点,结合装备的具体情况提出了基于改进GM(1,1)模型的导弹贮存可靠性预测方法。该方法首先利用"对数-幂函数变换"对导弹的历史可靠性数据进行处理,提高数据光滑度,然后依据GM(1,1)模型计算得到可靠性预测值和残差,再利用残差建立残差修正模型,得到残差修正值,减少残差对结果的影响,最后利用残差修正值修正可靠性预测值并还原,求得可靠性最终预测值。实例表明,该改进模型对导弹系统可靠性变化的描述比传统模型更加准确有效,预测结果精度更高,为导弹贮存可靠性预测分析提供了一种有效的改进方法,其算法设计推广性强,可作为其他装备寿命预估的重要工具。     

海洋移动目标多模型运动预测方法

分析海洋移动目标的运动特征,提出了预测前插值的灰色预测方法,改进了航迹变更预测和潜在区域预测模型。通过集成匀速运动预测、航迹变更预测、基于航迹的预测和潜在区域预测,提出多模型运动预测方法及其模型参数配置依据,根据滑动时间窗口中的观测数据与预测值的统计比较,评价不同预测方法的近期预测效果,决策下阶段适宜选择的预测方法。仿真实验表明多模型运动预测比使用单一运动预测方法降低预测风险,提高了预测精度。     

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.     

Progressive Type‐II censoring and coherent systems

A new connection between the distribution of component failure times of a coherent system and (adaptive) progressively Type‐II censored order statistics is established. Utilizing this property, we develop inferential procedures when the data is given by all component failures until system failure in two scenarios: In the case of complete information, we assume that the failed component is also observed whereas in the case of incomplete information, we have only information about the failure times but not about the components which have failed. In the first setting, we show that inferential methods for adaptive progressively Type‐II censored data can directly be applied to the problem. For incomplete information, we face the problem that the corresponding censoring plan is not observed and that the available inferential procedures depend on the knowledge of the used censoring plan. To get estimates for distributional parameters, we propose maximum likelihood estimators which can be obtained by solving the likelihood equations directly or via an Expectation‐Maximization‐algorithm type procedure. For an exponential distribution, we discuss also a linear estimator to estimate the mean. Moreover, we establish exact distributions for some estimators in the exponential case which can be used, for example, to construct exact confidence intervals. The results are illustrated by a five component bridge system. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 512–530, 2015     

On prediction intervals for normal samples

It is shown that many of the normal theory prediction intervals for statistics of random samples are still valid when the samples are correlated and have a specified covariance structure.     

灰色预测模型在非致命武器经济寿命预测中的应用

针对目前非致命武器经济寿命方面的研究相当缺乏的现状，结合非致命武器的自身特点，在全面分析装备全寿命周期费用的基础上，引入灰色理论，运用GM（1，1）模型对非致命武器的经济寿命周期费用进行估算和预测。通过分析，灰色预测模型具有较高的建模精度，预测方法和结果对非致命武器的经济寿命预测具有很强的实用性。     

Expansion planning for waste‐to‐energy systems using waste forecast prediction sets

We consider an expansion planning problem for Waste‐to‐Energy (WtE) systems facing uncertainty in future waste supplies. The WtE expansion plans are regarded as strategic, long term decisions, while the waste distribution and treatment are medium to short term operational decisions which can adapt to the actual waste collected. We propose a prediction set uncertainty model which integrates a set of waste generation forecasts and is constructed based on user‐specified levels of forecasting errors. Next, we use the prediction sets for WtE expansion scenario analysis. More specifically, for a given WtE expansion plan, the guaranteed net present value (NPV) is evaluated by computing an extreme value forecast trajectory of future waste generation from the prediction set that minimizes the maximum NPV of the WtE project. This problem is essentially a multiple stage min‐max dynamic optimization problem. By exploiting the structure of the WtE problem, we show this is equivalent to a simpler min‐max optimization problem, which can be further transformed into a single mixed‐integer linear program. Furthermore, we extend the model to optimize the guaranteed NPV by searching over the set of all feasible expansion scenarios, and show that this can be solved by an exact cutting plane approach. We also propose a heuristic based on a constant proportion distribution rule for the WtE expansion optimization model, which reduces the problem into a moderate size mixed‐integer program. Finally, our computational studies demonstrate that our proposed expansion model solutions are very stable and competitive in performance compared to scenario tree approaches. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 47–70, 2016     

The cost impact of using simple forecasting techniques in a supply chain

In this paper we consider an inventory model in which the retailer does not know the exact distribution of demand and thus must use some observed demand data to forecast demand. We present an extension of the basic newsvendor model that allows us to quantify the value of the observed demand data and the impact of suboptimal forecasting on the expected costs at the retailer. We demonstrate the approach through an example in which the retailer employs a commonly used forecasting technique, exponential smoothing. The model is also used to quantify the value of information and information sharing for a decoupled supply chain in which both the retailer and the manufacturer must forecast demand. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 388–411, 2003