基于组合预测模型的铁路货运量预测研究

为了进一步提高铁路货运量的预测精度,提出基于乘积季节模型与引入注意力机制(Attention Mechanism)的长短期记忆(Long Short-Term Memory)模型的组合预测模型.首先建立乘积季节模型、LSTM模型与引入注意力机制的LSTM模型,然后利用误差修正法分别将2种LSTM模型与乘积季节模型组合起...     

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高速铁路为人们提供了一种高效的运输方式.本文借鉴弹性系数法的相关理论,首先运用广义费用函数测算样本中高铁开通前后两地区综合客运成本的变化,结合两地区高铁开通前后客运量的变化得到了运输成本弹性系数,用于衡量两地区对于高铁开通的迫切性程度,从而在另一个层面衡量高铁建设的可行性.然后根据运输经济学及新经济地理学的相关理论,从人口、距离、人均GDP差异、平均人均GDP和产业结构相似度5个维度对样本的运输成本弹性系数进行建模,运用神经网络的方法来拟合其对运输成本弹性系数的影响情况,并以此为依据来测算北京市和张家口市对即将开通的京张高铁的迫切性程度.     

城市轨道交通网络化运营条件下车辆基地的资源共享要点

以《地铁设计规范》为依据,从车辆运用及维修角度,论述了城市轨道交通网络化运营条件下车辆基地的资源共享,包括车辆检修、段场共址建设、综合维修、物质供应和管理、技术培训、专用设备等方面的资源共享原则和注意事项。车辆基地资源共享不仅可满足车辆检修维保的功能需要,同时可有效避免或减少重复建设,节省工程投资,并提高资源利用效率,降低运营成本。     

滑坡监测无线传感器网络基于事件的信道分配方案

在高速铁路沿线的山体斜坡上部署无线传感器网络,用于监测山体斜坡变化情况。综合考虑传感器节点能量有限性和对采集信息的实时性需求,提出一个基于事件的信道分配方案用于滑坡监测信息的传输。以是否有列车经过山体斜坡区域作为事件,当无列车经过时,为节点分配活跃周期和睡眠周期,采用TDMA的方式唤醒节点并分配一个可用信道进行数据传输,从而在保证数据传输的前提下节省节点能量,延长网络寿命;当有列车即将经过时,节点完全进入活跃周期,采用多个信道并行传输的方式传输数据,减少传输过程中由于信息碰撞造成的信息丢失和重传,从而降低传输时延,提高信息传输的实时性。最后,通过仿真实验分析系统性能,证明所提方案的有效性。     

客运专线铁路隧道高陡坡洞口开裂整治技术研究

以宝兰客运专线塔稍村隧道为依托,分析隧道进口边坡及洞内裂缝的成因,评价边坡的稳定性,并提出具体的处理措施。对该隧道地层岩性、构造属性、围岩等级等进行阐述,针对该边坡建立系统的地表及洞内变形监测网并进行钻孔内位移测量工作,结合详细的地质调查,查明隧道进口处边坡、洞口挡墙、隧道内二衬裂缝的成因和基本特征,结合区段的工程地质特征,提出合理的工程处理措施,为类似工程的调查与处理提供参考。     

Connectivity analysis of the global shipping network by eigenvalue decomposition

ABSTRACT

Maritime shipping necessitates flexible and cost-effective port access worldwide through the global shipping network. This paper presents an efficient method to identify major port communities, and analyses the network connectivity of the global shipping network based on community structure. The global shipping network is represented by a signless Laplacian matrix which can be decomposed to generate its eigenvectors and corresponding eigenvalues. The largest gaps between the eigenvalues were then used to determine the optimal number of communities within the network. The eigenvalue decomposition method offers the advantage of detecting port communities without relying on a priori assumption about the number of communities and the size of each community. By applying this method to a dataset collected from seven world leading liner shipping companies, we found that the ports are clustered into three communities in the global container shipping network, which is consistent with the major container trade routes. The sparse linkages between port communities indicate where access is relatively poor.     

Obsolete Maps and Coastal Management: Case Studies from Northwest Ireland

On dynamic coastal sites, subject to rapid and sometimes unpredictable shoreline changes, management problems can be aggravated if legally authoritative maps are obsolete. These difficulties are illustrated by two case studies from County Donegal in northwest Ireland. The first case study outlines the problems that arise where statutory functional area boundaries are based on a near century-old map. The second case study deals with the problems of planning development on a site where a customized map only a few years old has been rendered obsolete by rapid coastal erosion. Other problems are caused by the inappropriate use of maps. Suggestions are made to mitigate the effects of outdated maps.     

Plate scanning tools to obtain travel times in traffic networks

The management of vehicle travel times has been shown to be fundamental to traffic network analysis. To collect travel time measurement, some methods focus solely on isolated links or highway segments, and where two measurement points, at the beginning and at the end of a section, are deemed sufficient to evaluate users' travel time. However, in many cases, transport studies involve networks in which the problem is more complex. This article takes advantage of the plate scanning technique to propose an algorithm that minimizes the required number of registering devices and their location in order to identify vehicles candidates to compute the travel times of a given set of routes (or subroutes). The merits of the proposed method are explained using simple examples and are illustrated by its application to the real network of Ciudad Real.     

多元评价体系组合模型在铁路隧道变形预测中的应用

为克服传统预测模型结构单一、预测精度及稳定性不足等缺陷,提出多元体系组合预测模型的建模思路。首先,基于支持向量机、BP神经网络及ARMA模型3种单一预测模型,构建铁路隧道变形预测体系;再以均方根误差、误差平方和及平均绝对误差等为评价准则或指标,构建各预测结果的误差评价体系,求解各单项预测模型的权值贡献指数,得到最优组合权值;然后利用后验差检验、残差检验和关联度检验构建预测精度校验体系,对组合预测结果进行检验,评价预测模型的有效性;最后,结合工程实例,对多元体系组合预测模型在特大断面隧道中的变形预测效果进行检验。结果表明:多元评价体系组合模型预测相对误差值均小于2%,具有较高的预测精度,且较单一预测模型具有更高的预测精度,也一致通过相关检验,验证了多元体系组合预测模型的有效性。     

基于 EM D桘BPN 方法的高速铁路短期客流预测

高速铁路短期客流预测是铁路运输系统的重要组成部分。无论是对列车开行方案的制定,还是对如何采取正确的营销策略,都具有重大的现实意义。通过混合经验模态分解方法和神经网络方法相结合的EMD-BPN方法来预测高速铁路短期客流量。组合方法主要分为三步：首先,使用经验模态分解方法将客流时间序列分解;其次,将IM Fs作为BP神经网络的输入;最后,应用神经网络对客流量做出预测。数值实例表明,该方法对于高速铁路短期客流预测在精度和稳定性上都有良好的表现。