索引查找最佳分块方法研究

分析索引查找算法中块内、块间查找方法的选择与时间复杂度的关系,给出具有最小渐近时间复杂度的最佳分块方法.     

基于贝叶斯网络的中医辨证系统

将贝叶斯网络运用于中医辨证系统的研究,以更加量化中医辨证诊断系统.通过将中医体系中的916个证候,51项证素及其构成的1700条证名构成中医辨证贝叶斯网络的节点集,初步建立起中医辨证数据库并通过网络学习,形成中医辨证贝叶斯网络结构及概率表.利用建立的贝叶斯网络中医辨证系统,进行数据计量分析、推理验证证候—证素—证名间的关系,其结果与中医专家经验有很高的吻合性,尽管其仍未能全面反映中医辨证的思维能力.所以贝叶斯网络是对中医辨证进行信息挖掘处理的一种较好方法,可应用于中医人工智能辨证系统的建立.     

考虑关键性的多约束下辐射干扰对消装备随舰备件配置优化方法

可用度是评估备件对装备完好性影响的重要指标,针对备件关键性对装备可用性造成影响而又难以将其考虑在内建立可用度模型的问题,以舰载通信电台辐射干扰对消装备为对象,采用对备件关键性实行专家打分的方法,将备件关键性作为备件配置优化的约束之一,建立以备件费用、备件体积、备件关键性为约束的备件配置优化模型。在备件费用、体积及关键性归一化的基础上,采用权重因子方法将多约束转化为单一约束,并给出了权重因子更新方法。列举案例,分别计算了费用约束、体积约束、关键性约束和多约束下的备件方案,并对比了装备改进前后的备件配置方案,将装备使用过程中的备件保障延伸至装备可靠性设计阶段。案例分析结果表明:备件配置方法在考虑了体积、费用等限制约束下,能同时兼顾备件关键性对装备完好性的影响;装备可靠性设计时,提高装备可靠性低的现场可更换单元(line replaceable unit, LRU)等薄弱点,能有效减少装备维修保障资源。     

动态分布式层次密钥管理

层次秘密通信在电子商务与电子政务以及其他的具有层次结构的系统中有广泛的应用,本文通过利用单向散列函数的不可逆计算的特性,设计了一个单向的等级加密体制的密钥管理方案,上级组结点可以安全容易的获取下级组结点的密钥,反之不然.并且在方案中实现安全组的动态添加、删除及更新组结点密钥.本方案计算量小、存贮要求低,并且可以实现分布式并行化计算.     

3GPP中分组交换流媒体服务的体验质量研究

在未来3G分组交换网络中,除了能向用户提供电信级的服务质量,还必须向用户提供最完美的体验质量. 体验质量不仅能描述用户感受,也可用来衡量业务可用度。在深入分析3GPP分组交换流媒体服务,体验质量的概念及其测量参数和协议的基础上,对如何评价和提高体验质量提出了基本的框架模型。     

稀浆封层路面层间黏结性能试验研究

为了对稀浆封层层间黏结性能进行评价,自行设计了以改进的剪切仪为基础的试验方法,能较好地模拟路面真实受力情况.试验结果说明,随着温度的升高,稀浆封层与沥青碎石下面层之间黏结强度在减小;不同的路面层间处理措施对黏结强度均有明显的影响;采用较大公称粒径的沥青混合料,或者对路面做凿毛处理均可以有效提高层间黏结强度.     

燃料电池汽车开发及产业化的关键技术研究

燃料电池电动汽车技术是当今世界上正在进行研究的一项高新技术,文章介绍了燃料电池电动汽车的动力系统和燃料电池系统的基本结构和工作原理。从燃料电池电动汽车的车身和底盘设计、燃料电池系统、驱动电机系统、电控系统以及系统优化等方面,分析了燃料电池电动汽车开发及产业化需要解决的关键技术,同时提出了相应的技术路线和对策。     

基于OpenSwan的动态VPN实现方案

IPsec是实现VPN的技术标准之一,而OpenSwan为Linux下IPsec的最佳实现方式,其最大程度地保证了数据传输中的安全性、完整性问题。OpenSwan不仅功能强大,其突出优点是一个开放源代码的项目,OpenSwan的实施应用不仅解决了无固定IP企业、单位网络的安全防护,也为企业节约资金和投资成果。实验证明,动态DNS方式是实现动态VPN系统的较有效方式。     

汽车转向柱管花键端部的强度研究

转向柱管是汽车转向系统中的重要部件之一,文章通过对某厂生产的汽车转向柱管总成试件的扭转破坏试验研究,结果证明在转向柱管靠凹槽一侧花键端部,通过增加转向柱管外花键齿与方向盘中心内花键齿之间的非接触区间长度,可以提高转向柱管所承受的最大扭矩的重要结论,从而为转向柱管的设计提供了理论依据.     

Intermittent demand forecasting in the Enterprise: Empirical verification

Forecasting methods are often valued by means of simulation studies. For intermittent demand items there are often very few non–zero observations, so it is hard to check any assumptions, because statistical information is often too weak to determine, for example, distribution of a variable. Therefore, it seems important to verify the forecasting methods on the basis of real data. The main aim of the article is an empirical verification of several forecasting methods applicable in case of intermittent demand. Some items are sold only in specific subperiods (in given month in each year, for example), but most forecasting methods (such as Croston's method) give non–zero forecasts for all periods. For example, summer work clothes should have non–zero forecasts only for summer months and many methods will usually provide non–zero forecasts for all months under consideration. This was the motivation for proposing and testing a new forecasting technique which can be applicable to seasonal items. In the article six methods were applied to construct separate forecasting systems: Croston's, SBA (Syntetos–Boylan Approximation), TSB (Teunter, Syntetos, Babai), MA (Moving Average), SES (Simple Exponential Smoothing) and SESAP (Simple Exponential Smoothing for Analogous subPeriods). The latter method (SESAP) is an author's proposal dedicated for companies facing the problem of seasonal items. By analogous subperiods the same subperiods in each year are understood, for example, the same months in each year. A data set from the real company was used to apply all the above forecasting procedures. That data set contained monthly time series for about nine thousand products. The forecasts accuracy was tested by means of both parametric and non–parametric measures. The scaled mean and the scaled root mean squared error were used to check biasedness and efficiency. Also, the mean absolute scaled error and the shares of best forecasts were estimated. The general conclusion is that in the analyzed company a forecasting system should be based on two forecasting methods: TSB and SESAP, but the latter method should be applied only to seasonal items (products sold only in specific subperiods). It also turned out that Croston's and SBA methods work worse than much simpler methods, such as SES or MA. The presented analysis might be helpful for enterprises facing the problem of forecasting intermittent items (and seasonal intermittent items as well).