沥青路面层间受力分析及加强层间黏结措施

基于沥青路面层间破坏原因,采用BISAR3．0软件对路面结构层间受力进行分析,探索了层间接触状态对路表弯沉及路面结构各层剪应力的影响规律,最后根据力学分析结论,提出加强路面层间黏结的措施,供相关施工参考。     

重点营运车辆的异常驾驶行为识别研究

为加强对重点营运车辆异常驾驶行为的监督与检测,本文基于时间序列符号化算法(TSA) 与多尺度卷积神经网络模型(MCNN)提出一种组合模型TSA-MCNN,用于识别重点营运车辆异常驾驶行为。首先,对北斗数据进行预处理,并基于营运车辆存在多种车型、多种速度限制、多种异常驾驶行为的特点划分4种异常驾驶行为,构建异常样本数据集。其次,构建TSA-MCNN模型识别样本数据集,其过程分为两阶段,第1阶段,针对重点营运车辆的特点,引入能够粗粒化处理数据特征的时间序列符号化算法与能够多通道参数输入的多尺度卷积神经网络进行组合,并基于Keras库完成TSA-MCNN模型的搭建;第2阶段,利用样本数据集作为模型的输入变量,完成模型的训练、测试与识别。最后,以广河高速重点营运车辆北斗数据验证TSA-MCNN模型的性能, 同时,与异常识别传统算法的卷积神经网络(CNN)模型与动态时间扭曲-K最近邻(DTW-KNN)模型进行对比分析。验证结果表明：TSA-MCNN模型整体识别准确率为97.25%,相对于CNN模型与DTW-KNN模型提高了20.50%与5.63%。其中,TSA-MCNN模型对于正常驾驶行为、超速驾驶行为、紧急停车行为、临时停车行为、低速驾驶行为的识别精确率相对于CNN模型(DTW-KNN模 型)分别提高了26%(13%)、26%(6%)、23%(5%)、28%(3%)、0(0),说明该模型对于重点营运车辆异常驾驶行为的识别具有良好的性能。     

Effect of open skies in the Middle East region

This research aims to estimate potential inter-regional passenger flows for air transport in the Middle East under open skies polices, once deregulation agreements are reached between neighboring countries. To arrive at reasonable demand estimates, Western and Eastern European demand data was analyzed as a first step, since it is assumed that current Middle Eastern demand is distorted as a direct result of regional political instability. The major factors affecting demand, based on the European dataset, included population size, gross domestic product (GDP) per capita, absolute difference in GDP per capita between two countries, great circle distance and membership of the European Union and World Trade Organization. Subsequently, a 21 country database was estimated for passenger flow in the Middle East region on an average peak season day. The demand estimations became input for a hub location model (p-hub median formulation) in order to achieve the second major aim of this research, objective identification of potential regional gateways. The results proved robust to both single and multiple allocation model assumptions, with Cairo and Tehran consistently achieving hub status, along with Istanbul and Riyadh, as the number of potential hubs increased. Finally, this research shows that under conditions of peace, given existing socio-economic indicators, inter-regional passenger demand flow could increase by upwards of 51% and regulatory authorities ought to consider the necessary infrastructure and demand management policies to enable the conservative regional demand growth estimated.     

Instrumented city database analysts using multi-agents

The Instrumented City (iC) database is a multi-purpose, transport-related database facility for use by the entire academic transport research community. Data from the UK Leicester City Council and Nottinghamshire County Council Traffic Management Computers is logged and archived on a continuous basis, by the Leeds University’s Institute for Transport Studies. Since its inception in 1992, the iC database has been used for various real-time applications such as air quality and noise monitoring, modelling and forecasting. This paper describes the framework that demonstrates the feasibility of using multi-agents as information analysts to process and manage the iC database. The agents are adaptive, interactive and personal. They can be trained via the interactions with the users to be personalised for individual preferences. These agents are designed to be responsible for (1) data clean-up to remove outliers; (2) missing data substitutions; (3) statistical data analysis; (4) data mining to enhance the understanding of the relationships between traffic and air quality, noise and health; and (5) knowledge discovery by identifying unknown but potentially important patterns.     

无线传感器网络中基于几何方法的覆盖洞检测

提出了一个基于几何方法的覆盖洞检测算法,用以在网络运行过程中找出覆盖洞,仿真结果表明:此算法在能量消耗和检测时间方面优于TBRA算法。     

一种双重时滞多重边复杂公交网络模型的同步研究*

在传统的建模方法的基础上,建立一种新的城市公交网络模型。根据4种不同的公交路线,通过引入时滞,将两重边复杂公交网络拆分为两个性质不同的子网络。进而研究具有双重时滞两重边复杂公交网络的全局自适应同步,给出自适应同步的一般条件。以 Lorenz系统为例,验证该方法的有效性。     

基于PSO的神经网络优化证券投资组合方法研究

针对传统人工神经网络中的BP(back propagation)神经网络自身局限以及其迭代次数多、收敛精度不高和泛化性差等缺点,提出了一种基于粒子群(particle swarm optimizer,PSO)算法的BP神经网络优化证券投资组合方法.在BP神经网络优化方法中,采用PSO算法替代了BP神经网络的梯度下降法,得到最优解,从而对BP神经网络模型进行优化.将该方法应用于证券投资组合的优化中,实验结果证明:该优化方法优于传统的BP神经网络优化方法.     

基于ANSYS的某墩式码头升级改造安全性评估方法研究

结合某实际工程,采用ANSYS建立两种有限元模型对码头进行安全性计算。结果表明,计算基床应力时应在沉箱与抛石基床间设置接触单元使计算结果更安全可靠,同时结合规范对码头抗滑稳定性、抗倾稳定性进行计算分析,采用ANSYS对码头进行安全性评估计算过程简便、计算结果准确。     

基于动态贝叶斯网络的调距桨任务可靠性模型及应用

为了解决调距桨在可靠性分析时动态的、可修复性的问题,引入了一种基于动态贝叶斯网络理论的新方法,提出了动态的和可修复的可靠性建模分析技术,弥补了传统方法在动态可靠性分析时模型描述上的局限性及算法上的缺陷问题。在模型方面,用贝叶斯网络能有效地刻画系统的动态行为、修复行为;在此基础上建立了系统任务可靠度数学模型,运用MATLAB软件中贝叶斯网络工具箱编写了MATLAB计算语句,输入有关元件的故障率与修复率能够实现推进装置的任务可靠性数值仿真。     

船用斜齿轮时变接触线对齿面摩擦力及摩擦扭矩的影响研究

文章在计算斜齿轮时变接触线基础上,采用数值编程快速计算主动轮齿面摩擦力和齿面摩擦扭矩。通过分析齿面摩擦力和齿面摩擦扭矩的均方根以及波动率后可知,时变接触线的波动是影响齿面摩擦力以及齿面摩擦扭矩的主要因素。在文中选定的参数范围内,齿面摩擦力的波动和齿面摩擦扭矩的波动与时变接触线的波动变化规律基本一致,呈现出一种10°-20°和20°-30°的变化规律,为工程减振降噪提供了理论参考。