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We investigate the relative effectiveness of top‐down versus bottom‐up strategies for forecasting the demand of an item that belongs to a product family. The demand for each item in the family is assumed to follow a first‐order univariate autoregressive process. Under the top‐down strategy, the aggregate demand is forecasted by using the historical data of the family demand. The demand forecast for the items is then derived by proportional allocation of the aggregate forecast. Under the bottom‐up strategy, the demand forecast for each item is directly obtained by using the historical demand data of the particular item. In both strategies, the forecasting technique used is exponential smoothing. We analytically evaluate the condition under which one forecasting strategy is preferred over the other when the lag‐1 autocorrelation of the demand time series for all the items is identical. We show that when the lag‐1 autocorrelation is smaller than or equal to 1/3, the maximum difference in the performance of the two forecasting strategies is only 1%. However, if the lag‐1 autocorrelation of the demand for at least one of the items is greater than 1/3, then the bottom‐up strategy consistently outperforms the top‐down strategy, irrespective of the items' proportion in the family and the coefficient of correlation between the item demands. A simulation study reveals that the analytical findings hold even when the lag‐1 autocorrelation of the demand processes is not identical. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007. 相似文献
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We consider the problem of assessing the value of demand sharing in a multistage supply chain in which the retailer observes stationary autoregressive moving average demand with Gaussian white noise (shocks). Similar to previous research, we assume each supply chain player constructs its best linear forecast of the leadtime demand and uses it to determine the order quantity via a periodic review myopic order‐up‐to policy. We demonstrate how a typical supply chain player can determine the extent of its available information in the presence of demand sharing by studying the properties of the moving average polynomials of adjacent supply chain players. The retailer's demand is driven by the random shocks appearing in the autoregressive moving average representation for its demand. Under the assumptions we will make in this article, to the retailer, knowing the shock information is equivalent to knowing the demand process (assuming that the model parameters are also known). Thus (in the event of sharing) the retailer's demand sequence and shock sequence would contain the same information to the retailer's supplier. We will show that, once we consider the dynamics of demand propagation further up the chain, it may be that a player's demand and shock sequences will contain different levels of information for an upstream player. Hence, we study how a player can determine its available information under demand sharing, and use this information to forecast leadtime demand. We characterize the value of demand sharing for a typical supply chain player. Furthermore, we show conditions under which (i) it is equivalent to no sharing, (ii) it is equivalent to full information shock sharing, and (iii) it is intermediate in value to the two previously described arrangements. Although it follows from existing literature that demand sharing is equivalent to full information shock sharing between a retailer and supplier, we demonstrate and characterize when this result does not generalize to upstream supply chain players. We then show that demand propagates through a supply chain where any player may share nothing, its demand, or its full information shocks (FIS) with an adjacent upstream player as quasi‐ARMA in—quasi‐ARMA out. We also provide a convenient form for the propagation of demand in a supply chain that will lend itself to future research applications. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 515–531, 2014 相似文献
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This article considers the problem of monitoring Poisson count data when sample sizes are time varying without assuming a priori knowledge of sample sizes. Traditional control charts, whose control limits are often determined before the control charts are activated, are constructed based on perfect knowledge of sample sizes. In practice, however, future sample sizes are often unknown. Making an inappropriate assumption of the distribution function could lead to unexpected performance of the control charts, for example, excessive false alarms in the early runs of the control charts, which would in turn hurt an operator's confidence in valid alarms. To overcome this problem, we propose the use of probability control limits, which are determined based on the realization of sample sizes online. The conditional probability that the charting statistic exceeds the control limit at present given that there has not been a single alarm before can be guaranteed to meet a specified false alarm rate. Simulation studies show that our proposed control chart is able to deliver satisfactory run length performance for any time‐varying sample sizes. The idea presented in this article can be applied to any effective control charts such as the exponentially weighted moving average or cumulative sum chart. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 60: 625–636, 2013 相似文献
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根据光学表面在微观结构呈现出的自相似性,利用尺度无关的分形模型描述了其结构特征;采用结构函数法对抛光表面的分形维数进行计算,分析了粗糙度参数RMS值、误差波长、测量尺度、采样长度和采样点数对分形维数的影响规律。在此基础上,提出了采用一阶自回归分形模型对抛光表面进行模拟的新方法,分析了界定尺度、模型参数对分形特征和分形维数的影响规律。利用分形维数描述光学表面的微观结构具有评价方法简单、在一定范围内与测量尺度无关等优点。 相似文献
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针对舰炮火控雷达高精度实时仿真建模的问题,运用高斯分布和正态平稳过程的两种误差序列生成方法,建立火控雷达简化仿真模型。通过对某火控雷达实测数据误差的统计及时序相关性分析,完成误差序列仿真生成与验证,给出了实现舰炮火控雷达探测误差仿真的优选方法。实践证明,正态平稳模型的误差生成方法可以有效满足新型舰炮仿真试验火控雷达建模要求。 相似文献
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针对直流位置伺服系统,提出了一种改进型IMC-PI控制方法。引入作用函数,并将其与IMC-PI控制器串联,构成改进型PI控制器,其中IMC-PI控制器根据内模控制原理进行设计,作用函数为系统偏差的微分表达式,其阶次的选择应保证系统开环传递函数为严格正则。改进IMC-PI控制可使系统的调节过程分为作用函数趋近零和保持为零的两个阶段,从而保证系统偏差按照作用函数等于零确定的轨迹趋近于零。仿真结果表明所提方法可使系统具有良好的动态响应性能和鲁棒性。另外,利用Qstudio RP实验平台跟随跟随1+sin(10t)rad正弦信号时,IAE为0.14 rad·s,实验结果表明该方法可有效改善伺服系统的性能。 相似文献
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An important phenomenon often observed in supply chain management, known as the bullwhip effect, implies that demand variability increases as one moves up the supply chain, i.e., as one moves away from customer demand. In this paper we quantify this effect for simple, two‐stage, supply chains consisting of a single retailer and a single manufacturer. We demonstrate that the use of an exponential smoothing forecast by the retailer can cause the bullwhip effect and contrast these results with the increase in variability due to the use of a moving average forecast. We consider two types of demand processes, a correlated demand process and a demand process with a linear trend. We then discuss several important managerial insights that can be drawn from this research. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 269–286, 2000 相似文献
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在实际工程中,常常需要利用模型去描述和分析问题。然而模型亦存在不确定性,即可能存在多个描述同一现象的模型,例如多个疲劳分析的模型。针对飞机结构的疲劳可靠性问题,提出在考虑三种裂纹扩展模型下基于贝叶斯公式的疲劳可靠度组合预测方法。针对不同应力水平下飞机结构试件的裂纹扩展数据建立了三种随机裂纹扩展模型;在考虑模型参数不确定性条件下,采用贝叶斯模型平均方法对三种模型进行组合;基于组合模型分析结构的可靠度。所提方法在分析飞机结构疲劳可靠度上,采用了组合模型,能够最大限度保障结果的稳定性。此外,考虑了模型参数的不确定性,能够得到更为合理的裂纹扩展预测分布和可靠度预测值。给出的实例及分析结果表明所提方法可行。 相似文献
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本文分析了坦克炮、反坦克炮简易火控系统自动调炮装置的结构特点及调炮误差变化规律,提出了工程上的校准方法及设计要点。 相似文献
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临近空间飞行器纵向逆控制系统设计 总被引:1,自引:1,他引:0
建立了临近空间飞行器无动力滑翔阶段的纵向运动模型,并应用动态逆方法推导了模型的逆系统.系统相对阶等于绕质心运动模型的系统阶数,实现了绕质心运动模型的线性化.为了克服纵向运动模型的隐动态和参数的不确定性,在内环动态逆控制器的基础上,设计了外环最优调节器.仿真结果表明:飞行器纵向逆控制系统可以准确跟踪俯仰角或攻角指令,并对参数不确定性和外界干扰具有较好的鲁棒性,具有工程适用性. 相似文献
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基于模糊时间序列的时变动态系统模糊建模 总被引:2,自引:0,他引:2
要想建立结构不确定、参数时变的动态系统的模型是很困难的。改进了Song Chisson的模糊时间序列方法,并成功应用于时变动态系统的辨识与建模和自适应控制。仿真结果表明该方法计算量小,实时性好,能很快地跟踪系统的变化。 相似文献
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介绍了基于客观数据的延迟时间模型参数极大似然估计方法,提出了应用优化理论中的单纯形法求解似然函数的算法,为延迟时间模型的参数估计问题提供了可行的解决方法。通过计算机模拟数据的验证,此方法切实可行,结果可以满足需要。 相似文献
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选取全球范围内72个基准站的坐标序列,采用改进的赤池信息量准则、贝叶斯信息量准则对不同噪声模型组合进行噪声分析,得到基准站坐标序列的最优噪声模型及速度参数,探讨时间序列跨度对噪声模型及速度估计的影响。结果表明,基准站坐标序列噪声模型不能由单一的噪声模型表述,其呈现出多样性特征,主要表现为幂律噪声、高斯马尔科夫噪声、闪烁噪声+白噪声特征,且三坐标分量表现出不同的噪声特性;随着时间跨度的增加,坐标时间序列的最优噪声模型、GPS站速度及其不确定度逐渐由发散趋于收敛,随机游走噪声模型的比重有所增加。结果表明10 a以上的时间跨度是较为理想的噪声模型估计尺度。 相似文献
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全球导航卫星系统(global navigation satellite system, GNSS)高程时间序列具有非平稳、非线性、含噪声等特点,在深入研究Prophet预测模型的基础上,针对Prophet预测模型对于趋势信号和周期信号有良好预测效果这一特性,提出一种引入经验模态分解(empirical mode decomposition, EMD)的“降噪—分解—预测”组合GNSS高程时间序列预测方法。该方法先将原始时间序列进行EMD降噪,再对降噪后的序列进行分解预测,最后重构各分量预测信号为最终预测序列。通过对实测高程数据进行研究,实验结果表明:降噪后信号的平均信噪比为10.30dB,能量百分比平均为88.75%;利用所构建的短期预测方法,GNSS高程时间序列预测结果的均方根误差分别平均提升26.41%和14.88%;平均百分比误差分别平均提升18.92%和7.91%,验证了组合预测方法的有效性及实用性。 相似文献
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云模型及其在指挥控制系统可靠性分析中的应用 总被引:7,自引:0,他引:7
根据指挥控制系统的特点及作战应用的具体情况,从指挥控制系统的可靠性出发,提出了适合指控系统可靠性分析的云模型。通过拟定性能评价指标,导出各指标的云模型及其多维加权综合云的重心,应用云重心评价方法进行分析;并通过案例,运用基于PC-L INM AP的云重心评价方法,以影响指挥控制系统可靠性的两个重要性能指标为依据,分析了未来联合作战中指挥控制系统的可靠性,比较贴近作战实际,可信度较高。 相似文献
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谢新艳 《国防科技大学学报》1999,21(6):119-122
讨论了一类多维双重时序AR(1)-MA(q)模型的二阶平稳性问题。通过导出一组线性方程组,给出了这类模型二阶平稳的显式充分条件和必要条件,为验证模型的二阶平稳性提供了一个可行的途径。 相似文献
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低速磁浮列车利用电磁吸力支撑车体,相比轮轨列车具有噪音小、转弯半径小、爬坡能力强等优点。研究控制器输出饱和条件下悬浮系统的稳定性问题,可以避免由于电网电压约束而可能出现的失稳现象,提高了系统运行的可靠性。基于磁浮列车单点悬浮模型,使用电流-位置双环设计方法设计得到可稳定悬浮的控制算法。由于磁浮列车悬浮控制器的输出饱和环节,进一步提出了一种基于搜索极大椭球的控制参数优化方法,在不改变控制算法设计的前提下实现了参数优化。通过仿真和试验均验证了优化后的控制效果,有效指导了实际系统的工程调试。 相似文献