基于脉搏波特征融合的驾驶疲劳检测方法

疲劳驾驶是交通事故的主要诱因之一,精确检测驾驶人的疲劳程度是主动预防疲劳驾驶事故的核心内容之一。通过开展自然驾驶试验,以驾驶人的生物信号脉搏波（Blood Pressure Waveform,BPW）为数据源,使用脉搏波波形分析方法从中提取有效表征驾驶疲劳的特征指标,构建用于检测驾驶疲劳等级的BPW特征指标集,在此基础上引入D-S证据理论建立了基于BPW特征融合的驾驶疲劳检测模型。结果表明：该模型对测试数据的疲劳驾驶理论检测精度达到了91.8%,优于贝叶斯网络模型的81.4%和支持向量机模型的84.3%,能够满足实际应用的需求,但与决策回归树检测模型99.7%的精度相比较还有差距。研究获得的基于生物信息融合的驾驶疲劳检查模型和方法在驾驶疲劳检测与监测中具有很好的应用前景,可为辅助安全驾驶和疲劳预警及主动干预提供新的技术方案。     

基于模糊证据理论的航道安全性评价

根据证据理论和模糊集理论,分析航道尺度、水文条件、运行强度和航标配置等影响航道安全的重要因素,建立模糊子集引入证据空间,结合专家意见得到模糊集合确定概率分配函数;并通过证据理论函数合成法则,得出航道安全系统的信任度函数.选取川江航槽中引航操作难度最大的航段--柴盘子航段(585.0～588.0 km/左槽)为例进行航道安全性评价,证明该方法在航道安全评估方面具有实用价值,可为航道、海事及船舶驾引人员的决策提供参考.     

汽车电气线路短路试验与鉴定技术的研究

一次短路熔痕、二次短路熔痕和搭铁短路熔痕是汽车火灾中常见的痕迹物证,本文首次提出在12V和24V汽车电源下,采用定性模拟试验的方法,分别制备了这3种熔痕样品,并对样品的宏观形貌、金相组织等进行分析、归纳和总结,最终得出结论:对汽车火灾中提取的导线熔痕进行宏观分析和金相分析等,可有效地判断导线熔痕的短路类型,给汽车火灾原因的认定提供重要的科学依据和技术支持。     

基于云模型与D-S证据理论的盾构施工隧道管片上浮风险评价

为定量评价分析盾构隧道管片的上浮风险并进行针对性的风险管控,以武汉地铁8号线黄浦路站-徐家棚站盾构区间段为 背景,构建隧道管片上浮风险评价指标体系和评价标准,建立基于云模型与D-S证据理论的盾构施工隧道管片上浮风险评价模型。 依据工程施工实测数据,对监测区段的上浮风险等级隶属度进行计算,经归一化形成证据并进行D-S证据融合; 基于条件化线性 组合规则,将历史证据与当前时刻证据进行证据更新,得出当前时刻该监测区间上浮风险的安全风险等级为较安全状态,最后针对 安全等级不高的材料因素给出相应的处理措施,为施工阶段隧道管片上浮风险评价与管理提供一种新的思路和方法。     

试析知识产权诉讼中证据失权规则存在的问题

知识产权案件专业性强、技术性强,案件审理过程中所遇到的证据规定的把握与运用影响重大．本文以证据失权规则为重点,分析在审理知识产权案件举证期限与证据交换规则中存在的问题与不足,以探寻完善证据失权制度的有效途径．     

基于神经网络和D-S证据理论的汽车电控系统故障融合诊断

在分析D-S证据理论和神经网络理论各自特点的的基础之上,提出将这两种方法进行融合,并对电控汽车车载自诊断系统的诊断数据流参数进行处理和分析.该融合方法是将各个独立的低维神经网络的输出值处理后作为辨识框架上命题的基本可信度,经过证据理论的再次融合后得到最终的诊断结果.通过电控发动机典型故障的实例分析表明,该方法能够克服单一神经网络诊断中数据源包含信息的不全面性以及模糊性等局限性,并使得证据理论的基本可信度分配不再完全依赖专家的主观化赋值,同时可以充分利用各种故障的冗余和互补信息,从而使得汽车电控系统的故障的识别能力得到提高.     

柴油机故障诊断中的变权重多证据体融合应用研究

为了能够确定各证据的权重,对证据进行权重调整,应用了基于遗传算法的加权平衡证据调整方法。首先,利用遗传算法确定最优化的或者近似最优化的权重系数,然后依据加权平均值和优先权的证据分布形态对证据进行加权调整,且保证调整后的证据加权平均值不变以及优先权证据分布形态稳定。柴油机故障诊断实例表明,采用基于遗传算法的加权平衡证据调整方法能提高故障诊断的信任度和准确率,明显优于普通D-S等权重证据组合方法。     

What are the determinants in making people free riders in proof-of-payment transit systems? Evidence from Italy

Nowadays, in proof-of-payment transit systems, fare evasion is provoking strong interest in public transport companies (PTCs) due to the relevant economic losses, social inequity and increased levels of violence affecting personal security. Therefore, there is the need to recognize possible fare evaders. By using 2177 on-board personal interviews, gathered from an Italian PTC, and logistic regression models, we isolate determinants of possible free-rider passengers and, hence, those whom it might be advisable to target in order to capitalize on the effect of the application of countermeasures on fare evasion put forward by the local PTC. We show that males, younger than 26 years, with a low education level, unemployed and/or students and without an alternative mode of transport other than the bus are more probably fare evaders. Moreover, people who make trips of shorter than 15 min, who are systematic users and are not satisfied with the service are possible fare evaders. Finally, we found that a low level of inspection, knowledge of fines and previous ticket violations are determinants which make people more prone to evade fares. These outcomes are very useful, because, to the best of our knowledge, they represent the first empirical contribution showing the determinants which help evaluate the propensity to be a fare evader, in probabilistic terms. Moreover, they could help PTCs understand who might be a fare evader, in order to anticipate suitable countermeasures.     

How much is too much for tolled road users: Toll saturation and the implications for car commuting value of travel time savings?

The current practice of forecasting the demand for new tolled roads typically assumes that car users are prepared to pay a higher toll for a shorter journey, and they will keep doing so as long as the toll cost is not higher than their current value of travel time savings. Practice ignores the possibility that there could be a point when motorists stop driving on toll roads due to a toll budget constraint. The unconstrained toll budget assumption may be valid in networks where the addition of a new toll road does not result in a binding budget constraint that car users may have for using toll roads (although it could also be invoked for existing tolled routes through a reduction in use of a tolled route). In a road network like Sydney which offers a growing number of (linked) tolled roads, the binding budget constraint may be invoked, and hence including additional toll links might in turn reduce the car users’ willingness to pay for toll roads to save the same amount of travel time. When this occurs, car users are said to reach a toll saturation point (or threshold) and begin to consider avoiding one or more toll roads. Whilst toll saturation has important implications for demand forecasting and planning of toll roads, this type of behaviour has not been explored in the literature. We investigate the influence that increasing toll outlays has on preferences of car commuters to use one or more tolled roads as the number of tolled roads increases. The Sydney metropolitan area offers a unique laboratory to test this phenomenon, with nine tolled roads currently in place and another five in planning. The evidence supports the hypothesis that the value of travel time savings decreases as a consequence of toll saturation.     

基于多分类支持向量机和D-S证据理论的轴承故障诊断

针对支持向量机( SVM)硬判定输出分类结果缺乏定量评价的问题,提出了一种多分类SVM后验概率建模的改进方法。通过引入D-S证据理论,得到多分类SVM在D-S证据理论识别框架下的基本概率分配,使样本在分类时同时具有定性解释和定量评价。接着,将多源信息送入SVM之后在决策级对多个SVM分类输出进行证据融合,以提高诊断精度。最后,将该方法应用于轴承故障的诊断中。结果表明,该方法能正确分类采用单源信息时所错分样本,降低识别的整体误差,显著提高故障诊断的准确性。