黄土沟壑区湿软路基沉降预测模型

为合理考虑路基沉降预测时诸多影响因素的不确定性与随机性,提出基于神经网络范例推理的路基沉降预测模型。以同类工程的成功经验为基础,建立了基于神经网络的沉降范例检索模型,在范例相似度计算中,引入归一化效用函数,通过神经网络的学习,建立当前沉降范例与沉降源范例之间的相似关系,最终实现当前沉降范例的沉降预测。对黄土沟壑区湿软路基沉降预测结果表明,该模型具有较高的预测准确性,预测值与实测值绝对误差小于10%。     

The use of demand correlation in the modeling of air carrier departure delays as first‐order autoregressive random processes

A method for modeling air carrier departure delays at commercial‐service airports as autoregressive random processes is presented. This method employs the correlation of a priori demand data to significantly reduce prediction error in the optimal least‐squares estimator for additive white noise. The reduction factor of the prediction error is demonstrated to be on the order of 10² over that of the unbiased estimator. Copyright © 2011 John Wiley & Sons, Ltd.     

CTCS-2级列控车载设备机车信号故障分析探讨

概述CTCS-2级列控车载设备机车信号的工作原理,通过具体案例分析无法接收机车信号信息的原因,详细阐述故障处理的方法,归纳总结故障处置流程。     

基于GRNN的GSM-R场强覆盖预测算法

在比较Hata模型修正方法和GRNN算法场强覆盖预测效果的基础上,仿真分析了训练集构成和平滑因子选择对GRNN算法预测效果的影响,给出了训练集构成和平滑因子选择的方法;提出了电波传播环境相似系数来表征GRNN模型在不同环境下的适用性。仿真结果表明,两种传播环境的相似系数越大,由一种环境下测试数据确定的GRNN在另一环境下的预测精度越高。     

基于社交网络的民航旅客偏好建模

从社会网络的视角，提出了一种旅客个体偏好与关系偏好相结合的建模方法．首先，从旅客的历史出行记录中，构建基于共同出行关系的旅客社会网络；然后，构建旅客个体偏好模型和旅客关系偏好模型；最后，基于旅客偏好模型给旅客推荐座位．在民航领域的一个真实的数据集上进行了实验，证明本文提出的偏好模型能够有机地将旅客个体偏好与关系偏好结合起来，较好地描述旅客对航班座位的偏好．     

Resolving the property right of transportation emissions through public–private partnerships

The application of public–private partnerships (P3’s) in the transportation sector has grown in popularity worldwide. Despite this important shift in the provision of transportation service, there are clear gaps in knowledge about the impacts of P3 projects, especially on emissions from transportation systems as a whole. Not only should policy makers evaluate the emissions impacts from P3 projects, but they should also think about innovative models that address or charge for emissions into P3 contracts. This addition to P3 contracts could provide a new solution to the long-existing property right paradox: who owns (is responsible for) emissions from transportation systems? This study attempts to fill the research gap by analyzing these innovative models. Using the road network of Fresno, California, as our case study, we offer a number of interesting insights for policy makers. First, average peak emissions costs range from 1.37 cents per mile (the do-nothing case) to 1.20 cents per mile (profit-maximizing cases) per vehicle. Although emissions costs from the P3 projects are lowest for the profit-maximizing cases, the system-wide emissions costs of these cases are highest because of spillover effects. Second, charging project owners for the emissions costs of P3 projects is not an effective way to reduce emissions or the total costs of travel, especially on a VMT basis. Instead, the public sector should implement emissions-included social cost-based price ceilings. When employing these limits, project owners could still be charged for the emissions costs. Finally, using total travel time as the only objective function for evaluating P3 projects can be misleading. Several P3 projects have shown better outcomes using total travel cost with the inclusion of emissions and fuel consumption costs, instead of using total travel time as the only objective function.     

短时段交通流预测的RBF神经网络模型

介绍了基于RBF神经网络的短时段交通量预测模型,并利用该模型对高速公路所采集的数据进行仿真预测分析。预测结果表明RBF神经网络预测方法通过定义合理的网络结构参数可以获得较高的预测精度,能够满足路网调度对短时段交通流预测的需求。     

基于神经网络的高速公路出入口OD矩阵估计方法研究

通过高速公路出入口OD矩阵计算,得到高速公路的断面交通流量,这些数据对于高速公路各项管理措施的制定是非常重要的.针对高速公路出入口OD矩阵推算方法中假设每一留线车辆以等概率驶离高速公路的不足,提出了基于改进BP神经网络的高速公路出入口OD矩阵推算模型,并设计了OD推算神经网络.实例分析表明,该模型推算结果理想,且推算精度得到一定提高.     

汽车操纵稳定性主客观评价数据的一种处理方法

汽车操纵稳定性主客观评价之间的相关性分析是汽车技术的重要课题。提出了汽车操纵稳定性主客观评价数据的一种处理方法．通过回归分析筛选客观参数，运用BP神经网络建立相关性模型，验证结果说明了该方法的可行性。     

非港湾式停靠站对路段通行能力的影响研究

分析了路段上非港湾公交车站对路段通行能力有影响的6个因素,在实地调查的基础上,运用VISSIM进行试验仿真,得到大量数据,定量分析了各影响因素对路段通行能力的影响。建立神经网络模型对仿真数据进行分析,得到一组权值和偏差矩阵数据,通过该数据以及神经网络模型,可以在不同条件下,得到非港湾停靠站对路段通行能力的影响系数。