基于Box-Cox-TQR概率密度的铁路运用车保有量预测方法

合理的铁路运用车保有量，对满足铁路货运需求，提高货车运用效率，降低运营成本等有重要作用.考虑铁路运输系统复杂的内外部环境及其动态变化特性，对影响运用车保有量因素定性分析；提出了粗糙集属性约简、灰色关联分析、逐步回归方法相结合的主要影响因素识别方法.以此为基础，建立了基于 Box-Cox变换分位数回归(Box-Cox-TQR)和核密度估计相结合的概率密度预测模型.以国家铁路局运用车保有量实际数据为基础，进行预测试验.结果表明，利用主要因素识别的方法符合目标值的运动变化规律，预测结果具有良好的精度.此外，概率密度预测比点预测、区间预测传递出更多信息，为管理决策提供更多准确有用信息.     

User-centric interdependent urban systems: Using time-of-day electricity usage data to predict morning roadway congestion

Urban systems are interdependent as individuals’ daily activities engage using those urban systems at certain time of day and locations. There may exist clear spatial and temporal correlations among usage patterns across all urban systems. This paper explores such a correlation among energy usage and roadway congestion. We propose a general framework to predict congestion starting time and congestion duration in the morning using the time-of-day electricity use data from anonymous households with no personally identifiable information. We show that using time-of-day electricity data from midnight to early morning from 322 households in the City of Austin, can make reliable prediction of congestion starting time of several highway segments, at the time as early as 2 am. This predictor significantly outperforms a time-series predictor that uses only real-time travel time data up to 6 am. We found that 8 out of the 10 typical electricity use patterns have statistically significant affects on morning congestion on highways in Austin. Some patterns have negative effects, represented by an early spike of electricity use followed by a drastic drop that could imply early departure from home. Others have positive effects, represented by a late night spike of electricity use possible implying late night activities that can lead to late morning departure from home.     

基于模式预测法的城市轨道噪声影响研究

为研究城市轨道交通高架线两侧噪声传播特点与规律,探索声环境敏感点的降噪防治措施,以拟建成都地铁5号线工程为研究对象,选取适合的预测模式,确定出各个技术参数并模拟计算出噪声预测结果,通过类似既有上海轨道5号线工程的大量实测数据有效验证了预测结果的正确性和可靠性。在此基础上的研究结果表明:水平方向上桥梁两侧声影区内,噪声级随着距离增加而增强;而在声照区内,噪声级则随距离的增加而减弱。垂直方向上高架线噪声影响最严重区域为周边建筑物5层楼附近,因此要特别关注并加强该区域的降噪治理工作。     

Real time traffic flow outlier detection using short-term traffic conditional variance prediction

Outliers in traffic flow series represent uncommon events occurring in the roadway systems and outlier detection and investigation will help to unravel the mechanism of such events. However, studies on outlier detection and investigations are fairly limited in transportation field where a vast volume of traffic condition data has been collected from traffic monitoring devices installed in many roadway systems. Based on an online algorithm that has the ability of jointly predict the level and the conditional variance of the traffic flow series, a real time outlier detection method is proposed and implemented. Using real world data collected from four regions in both the United States and the United Kingdom, it was found that outliers can be detected using the proposed detection strategy. In addition, through a comparative experimental study, it was shown that the information contained in the outliers should be assimilated into the forecasting system to enhance its ability of adapting to the changing patterns of the traffic flow series. Moreover, the investigation into the effects of outliers on the forecasting system structure showed a significant connection between the outliers and the forecasting system parameters changes. General conclusions are provided concerning the analyses with future work recommended to investigate the underlying outlier generating mechanism and outlier treatment strategy in transportation applications.     

汕头市第二条过海水管顶管工程导向测量

该文以汕头市第二条过海水管顶管工程为例,确定了该顶管的贯通误差指标,对顶管导向测量期间的几项测量工序进行了横向误差的分配,包括控制测量,顶进孔和接收孔中心坐标测量,工作井内导向短基线测量,以及顶管施工过程中工具头后座中心的偏差测量等。通过该导向测量最终保证顶管的顺利贯通。     

公路网规划方法简介

为实现公路交通发展的目标，研究适合本地区的公路网规划方法，旨在寻求本地区发展规划与公路网空间布局的协调关系．建立与本地区发展新格局相适应的路网规划体系。     

CRTSⅢ型无砟轨道冬季温度场特性

为研究CRTSⅢ型无砟轨道温度场分布规律,在昌赣客运专线外进行足尺无砟轨道板温度场监测,基于统计学原理分析冬季轨道结构温度变化规律并提出适合CRTSⅢ型无砟轨道的竖向温度梯度预估模型.研究结果表明:CRTSⅢ型无砟轨道结构温度场受外界环境影响较大,其中轨道板顶面温度变化最为明显,沿深度方向各结构层温度峰值有明显的滞后现象;竖向温度梯度大于横向温度梯度,对结构温度影响起主导作用;日太阳辐射总量和最大温度梯度具有较好的相关性,据此建立了冬季日最大温度梯度经验回归公式,可为不同气候条件下的CRTSⅢ型无砟轨道的温度梯度研究提供参考.     

基于神经网络的公路工程承发包价格发展预测

公路工程承发包价格是公路工程造价研究的重要内容。合理确定影响公路工程承发包价格的多种因素,采用基于BP神经网络的公路工程价格预测方法,建立模拟承发包价格与其影响因素间的非线性关系预测模型,经过训练与检验、数据预测,结果表明,该方法实用性强,具有一定的理论与实际应用价值。     

水下单层圆柱壳振动声辐射预报的测点布置改进方法

为解决水下单层圆柱壳结构振动声辐射预报中的测点布置问题,本文提出一种测点布置改进方法——均匀子集随机选取测点方法。该方法将所有待选测点分成相互独立的均匀子集,然后从各个子集中随机选取一个测点,再通过目标函数对每组测点进行评价,从而选择出好的测点组合。通过与均匀布置方法得到的振动声辐射预报结果对比表明,本文提出的均匀子集随机选取测点方法不仅保证较高的振动声辐射预报精度,且避免均匀布置方法中测点选择的主观性和盲目性,是一种优秀的测点布置方法。     

动态管理模式下路侧停车泊位占有率预测方法

城市停车已逐步实现信息化和动态化管理，本文对动态管理模式下大范围路侧泊位占有率预测方法进行研究.在收集美国旧金山492万条停车交易数据的基础上，利用可同时提取数据空间关联和时序趋势特征的卷积长短时记忆神经网络(Convolutional LSTM Network，ConvLSTM)，分别构建考虑停车费率和时限动态变化的有政策模型，和没有动态管理信息输入的无政策模型.结果显示，有政策模型的训练效率和预测精度会显著提升.在政策平稳阶段，两种模型均能够有效预测泊位占有率；在政策发生变化时段，无政策模型的预测误差出现激增，但有政策模型的预测误差依然保持平稳，表明本文提出的方法能够很好地应对动态管理模式下停车需求的变化.