故障树与专家规则的车载故障诊断专家系统

文章旨在开发一种随车故障诊断专家系统,指导用户自行排除故障。提出了将故障树分析法与基于规则的专家系统相结合构建的故障诊断专家系统;以Windows CE和S3C2440A为平台,以EVC＋＋为编程语言,开发出具有友好的人机交互界面车载汽车故障诊断专家系统,该系统通过用户选择故障现象,便提示可能发生的原因和维修建议;并以发动机无力为例进行诊断,验证了该系统的有效性和实用性。该系统具有一定的创新性,对我国汽车修理行业具有很大的实用价值。     

基于组合实物期权的船舶投资决策研究

旨在研究具有组合复合实物期权特征的船舶投资决策。通过建立二叉树定价模型,并利用Crystal Ball软件运用蒙特卡洛模拟方法模拟航运市场波动率,从而对船舶投资项目进行评价。通过实例分析得出,拥有多重选择性的船舶投资项目的价值要大于仅有单一期权的投资项目价值。     

基于Microsoft时序算法的广东省交通运输领域能耗预测研究

通过收集历史数据,建立多个影响城市交通能耗的因素与交通运输能耗的数据库,首先用决策树算法对影响因素进行选择,然后根据给定的输入列,用Microsoft时序算法对广东省交通能耗进行短期预测。结果表明,运行的车辆数、车辆的周转量是影响能耗的两大主要因素,同时短期内交通能耗呈上升趋势,且较往年有所增强。     

民航运输航空器着陆阶段偏出跑道事件分析模型

为了克服故障树分析方法只能描述正常和故障两种状态的缺陷,利用故障树方法的逻辑分析优势,以及贝叶斯网络描述多态事件和计算概率的功能,建立了基于故障树和贝叶斯网络相融合的航空器着陆偏出跑道事件分析模型,提出了故障树与贝叶斯网络之间的转换算法求解该模型.根据1996—2010年中国民航着陆偏出跑道事件的数据,确定了着陆航空器偏出跑道的主要原因,并按重要程度进行了排序.研究结果表明:积水、反喷或减速板故障、复杂气象条件、驾驶术欠缺、前轮转弯卡阻、夜航或受灯光不利影响、对机组资源管理失效、积冰积雪是导致着陆偏出跑道的主要风险因素,其后验概率均大于0.3;应针对主要风险因素,制定针对性预防措施.      

基于ID3算法的卷烟产品零售客户分类研究

ID3算法是一种比较高效的数据挖掘算法,通过这一算法在卷烟产品零售客户分类上的运用,快速的将零售客户归入不同的类别,实现了依据客户重要性和产品依存度提供针对性的服务,以此来制定更加合理的卷烟产品营销策略,从而优化资源配置,提高销售额。     

基于加权相对熵的二阶马尔可夫模型的进化树重构

利用加权相对熵的二阶马尔可夫模型的基本原理,对DNA序列进行比较.DNA序列由4个字符A、T、C、G构成的序列,将其视为一个马尔可夫链,取状态空间Ι={A,T,C,G},使用二阶转移概率矩阵来描述DNA序列,得到DNA序列的特征值,进而利用特征值定义DNA序列的相似性度量,得到能够对DNA序列进行比较的新方法,并利用这个方法对30个物种的线粒体DNA序列进行分类,通过加权相对熵得到距离矩阵的非比对方法构建的进化树划分更加清晰,准确度更高.     

Refining light rapid transit typology: a UK perspective

Abstract

Recent developments in the light rapid transit sector have introduced transit modes that are attempting to imitate the performance of others, e.g. buses with tram-like characteristics. The boundaries between existing definitions of what is a bus, tram or train are becoming blurred. For transport studies and practice this requires a review of how we define modes. This is not just a matter of semantics, but has safety and competition regulation implications for system operators. This paper proposes a structure to produce rail- and bus-based transit mode definitions and typology that are appropriate for modern use. A decision tree is used to classify and define the transit modes as guided-bus, trolley-bus, light rail and tram-train and is provided with example systems. The paper provides a robust definitional framework that allows transit system promoters, operators and other interested parties to have a consistent basis of reference when specifying and comparing rapid transit systems.     

Modelling heavy vehicle car‐following behaviour in congested traffic conditions

This study develops a car‐following model in which heavy vehicle behaviour is predicted separately from passenger car. Heavy vehicles have different characteristics and manoeuvrability compared with passenger cars. These differences could create problems in freeway operations and safety under congested traffic conditions (level of service E and F) particularly when there is high proportion of heavy vehicles. With increasing numbers of heavy vehicles in the traffic stream, model estimates of the traffic flow could be degrades because existing car‐following models do not differentiate between these vehicles and passenger cars. This study highlighted some of the differences in car‐following behaviour of heavy vehicle and passenger drivers and developed a model considering heavy vehicles. In this model, the local linear model tree approach was used to incorporate human perceptual imperfections into a car‐following model. Three different real world data sets from a stretch of freeway in USA were used in this study. Two of them were used for the training and testing of the model, and one of them was used for evaluation purpose. The performance of the model was compared with a number of existing car‐following models. The results showed that the model, which considers the heavy vehicle type, could predict car‐following behaviour of drivers better than the existing models. Copyright © 2013 John Wiley & Sons, Ltd.     

复制窗口不等保护喷泉码的与或树渐进性能分析

采用与或树分析方法,结合算法的构造,推导出复制窗口不等保护算法中各类数据的译码失败概率迭代公式.从数学的角度验证算法性能.通过Matlab性能仿真,给出在不同复制因数下复制窗口不等保护算法与算法误比特率性能关系曲线.通过与基于权重的不等保护算法及拓展窗口喷泉码的渐进性能仿真结果进行对比,证明了该算法在相同译码开销下,可将保护级别提高3~4个数量级.此外,本文研究了复制因数对算法性能的影响,在不同的译码开销下,通过Matlab仿真给出复制因数与算法性能的关系曲线.     

高速公路尾随相撞事件的贝叶斯网络致因分析模型

应用上海市高速公路1104条事件数据,基于专家知识和数据融合方法建立贝叶斯网络结构;利用服从Dirichlet分布的贝叶斯方法进行参数学习;运用团树传播算法进行推理分析。研究了上海市高速公路尾随相撞事件类型与不同道路环境条件之间的关系。在验证贝叶斯网络模型的有效性后,系统分析事件致因,并提出改进措施。发现重大尾随相撞事件易发生在大中型车与小型车之间;夜间易发生大中型货车的重大尾随相撞事件,尤其是凌晨0时至6时;路表潮湿状态下的非普通路段上易发生大中型客车的重大尾随相撞事件。结果表明贝叶斯网络建模能够更好的反映事件致因因素的多维性及关联性,是交通事件致因分析的有效方法。