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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. 相似文献
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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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借鉴体系结构能力视角需求分析方法,根据数字化机步师指挥信息系统支撑能力的内涵,设计了6种新的能力视角模型,通过深入分析能力构想、能力结构、能力关系,以及5种体系级能力与系统组成、作战指挥活动、作战信息流程之间的映射关系,理清了指挥信息系统作战运用的能力需求。分析结果可为数字化机步师指挥信息系统的编配、运用与评估提供科学依据和理论指导。 相似文献
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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. 相似文献
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基于活动方法的武器装备型号论证需求分析 总被引:1,自引:0,他引:1
为了适应信息化战争以及基于能力的装备建设需要,武器装备型号论证不能局限于该型号装备承担的基本作战任务,必须面向体系结构展开需求分析。探讨了武器装备型号论证需求分析内涵及本质,给出了理论依据和指导;明确了基于活动方法的原理,对方法的应用提出了要求和规范;借鉴美军体系结构有关技术,从作战任务和装备系统2个方面展开需求分析,提出了作战、装备和能力需求之间的追溯关系矩阵,构建了基于活动方法展开武器装备型号论证需求分析的具体步骤。为武器装备型号论证需求分析提供了有力的方法支撑,有助于需求分析的工程化。 相似文献
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目前军事需求的描述方法主要是理论研究为主,无法较好应用于我军的需求开发实践.根据我军联合作战指挥信息系统的需求开发经验,提出了一种可行的C4ISR需求描述模型,首先分析了需求建模所涉及的要素及其关系,提出了C4ISR需求模型的概念,然后以图形化和形式化两种形式分别对用户模型、活动模型、信息模型和功能模型等4个方面进行了需求描述方法的研究. 相似文献