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来进行预测,最后将预测结果分别与单一模型进行对比。采用2005年至2018年全国铁路月度货运量进行预测分析,结果表明2种组合预测模型的预测精度均高于单一预测模型的预测精度,其中基于乘积季节模型与引入注意力机制的LSTM模型的组合预测模型精度最高,具有研究和实用价值。     

岩溶区地铁隧道下穿跨河桥梁施工技术研究

以贵阳轨道交通2号线下穿南明河及团坡桥为工程依托,针对岩溶发育区不均匀浅覆土条件下地铁隧道穿越跨河桥梁施工中遇到的抗渗防沉等难题,在遵循浅埋暗挖法十八字方针的基础上进行方案优化。下穿施工前对河床低洼处进行回填,同时增设水平隔水层,初步解决了河水下渗难题。隧道开挖过程中在掌子面进行全断面帷幕注浆及超前管棚支护确保了拱顶的稳定性,采用悬臂掘进机掘进使地层沉降得到控制,二衬混凝土浇筑时采用缺陷预控技术避免了二衬背后出现空洞,同时采用动态监控量测,有效解决了围岩稳定及团坡桥沉降的难题。     

Integrated models of land use and transportation for the autonomous vehicle revolution

ABSTRACT

The advent of the autonomous vehicle (AV) will affect not only the transportation system, but also future patterns of land development. Integrated land use and transportation models will be critical tools in assessing the path forward with this technology. Key questions with respect to land use impacts of AVs arise from potential changes in sensitivity to travel and reduced demand for parking. It is an open question whether AVs will induce urban sprawl, or whether spatial economies of agglomeration will mitigate any reductions in travel time sensitivity. The deployment of shared fleets of AVs would likely reduce parking demand, producing yet to be explored impacts on property development within existing urban footprints. We perform a critical assessment of currently operational models and their ability to represent the adoption of AVs. We identify the representation of time in such models as a vital component requiring additional development to model this new technology. Existing model applications have focused on the discrete addition of new infrastructure or policy at a fixed point in time, whereas AV adoption will occur incrementally through time. Stated adaptation surveys are recommended as tools to quantify preferences and develop relevant model inputs. It is argued that existing models that assume comparatively static equilibrium have been convenient in the past, but are insufficient to model technology adoption. In contrast, dynamic model frameworks lack sufficient structure to maintain reasonability under large perturbations from base conditions. The ongoing advancement of computing has allowed models to move away from being mechanistic aggregate tools, towards behaviourally rich depictions of individual persons and firms. However, much work remains to move from projections of existing conditions into the future, to the evolution of the spatial economy as it evolves through time in response to new technologies and exogenous stresses. Principles from complex and evolutionary systems theory will be important in the development of models with the capacity to consider such dynamics.     

滇西地区复杂地质条件下隧道施工技术研究

随着经济社会的快速发展,我国西南地区公路、铁路、城市轨道交通等建设密度越来越高。西南地区地质构造复杂,隧道施工难度大,施工工期长。为了提高隧道施工进度及安全性,施工方法的选择尤为重要。围岩的自稳能力决定了施工方法的选择,无论何种施工方法,均应在围岩自稳时间内完成初期支护,确保围岩稳定,防止隧道塌方、变形。基于围岩自稳时间的三台阶施工方法,在各个工序中加入时间要素,改变了开挖工法频繁转换的现状,做到了复杂地质条件下快挖、快支、快成环,提高了隧道施工进度,保证了施工安全。     

岩石掘进机关键技术展望

经过5个阶段的发展,TBM在我国的应用正在不断推广,应用前景十分光明,挑战也十分严峻。简要总结我国TBM研究与应用的5个发展阶段和应用前景,分析TBM施工面临的6大挑战： 地质多样化带来更多的地质风险; 应用领域亟待拓展; 设备技术发展赶不上施工需求的变化; 施工进度不均衡; 施工环境越来越严苛; 存在不合理的施工合同。从TBM设计制造及施工应用的9个方面提出展望： 核心部件国产化; 提升各种地质条件下的破岩能力; 提高出渣能力及可靠性; 提升初期支护及超前加固性能; 研发异形断面TBM; 圆形断面TBM开挖隧道的空间合理利用; 大力推动TBM周转使用和再制造TBM应用; 研究极端恶劣地质条件下TBM施工技术; 促进国产配套施工设备研发应用。只有不断深入研究TBM设备与施工的关键技术及前沿技术,有效解决设备设计制造和施工过程中遇到的难题,才能不断提升我国TBM设备与施工技术水平,避免陷入关键技术受制于人的窘境,促进我国TBM事业持续健康发展。     

岩溶富水区深埋水沟排水隧道注浆圈参数研究

为合理确定深埋水沟排水方式下隧道注浆圈特征参数,以某岩溶富水区隧道工程为依托,采用FLAC3D软件建立流固耦合计算模型,针对其注浆圈参数进行合理探讨,研究注浆圈厚度、注浆圈渗透性对隧道涌水量、衬砌水压力、结构安全性的影响规律。研究结果表明： 增加注浆圈厚度或降低注浆圈渗透性可降低衬砌水压、控制涌水量、保障结构安全,但并不代表实际工程中注浆参数需要追求最值,而应兼顾安全性和经济性,选取相对合理的注浆参数;结合模拟计算结果与同类工程案例,建议依托工程注浆圈厚度以5～6 m、渗透性比值以注浆前的1/50（渗透系数为2×10-6 cm/s）为宜,并应结合实际进行技术经济对比,合理确定现场注浆参数。     

Forecasting container throughput based on wavelet transforms within a decomposition-ensemble methodology: a case study of China

To improve predictive accuracy, new hybrid models are proposed for container throughput forecasting based on wavelet transforms and data characteristic analysis (DCA) within a decomposition-ensemble methodology. Because of the complexity and nonlinearity of the time series of container throughputs at ports, the methodology decomposes the original time series into several components, which are rather simpler sub-sequences. Consequently, difficult forecasting tasks are simplified into a number of relatively easier subtasks. In this way, the proposed hybrid models can improve the accuracy of forecasting significantly. In the methodology, four main steps are involved: data decomposition, component reconstruction based on the DCA, individual prediction for each reconstructed component, and ensemble prediction as the final output. An empirical analysis was conducted for illustration and verification purposes by using time series of container throughputs at three main ports in Bohai Rim, China. The results suggest that the proposed hybrid models are able to forecast better than do other benchmark models. Forecasting may facilitate effective real-time decision making for strategic management and policy drafting. Predictions of container throughput can help port managers make tactical and operational decisions, such as operations planning in ports, the scheduling of port equipment, and route optimization.     

基于灰岩地质隧道高边坡压力分散性锚索应用研究

本文结合实际工程案例,通过理论推导、对比分析,探讨了压力分散型锚索在灰岩地质条件下锚固段应力、岩体蠕变和张拉方式对锚索的影响,并取得以下成果:(1)推导出压力分散型锚索的切应力和轴力公式,对锚索在特殊地质条件下的设计及应用提供参考;(2)考虑岩体的蠕变效应,并推导其本构方程;(3)利用不同荷载张拉后补偿张拉最后整体张拉的方式,有效改善了压力分散型锚索因锚固段长度不同导致应力集中产生破坏的问题,并与监测值进行对比分析,以验证张拉方式的正确性。     

Development of railway station choice models to improve the representation of station catchments in rail demand models

ABSTRACT

This paper describes the development of railway station choice models suitable for defining probabilistic station catchments. These catchments can then be incorporated into the aggregate demand models typically used to forecast demand for new rail stations. Revealed preference passenger survey data obtained from the Welsh and Scottish Governments was used for model calibration. Techniques were developed to identify trip origins and destinations from incomplete address information and to automatically validate reported trips. A bespoke trip planner was used to derive mode-specific station access variables and train leg measures. The results from a number of multinomial logit and random parameter (mixed) logit models are presented and their predictive performance assessed. The models were found to have substantially superior predictive accuracy compared to the base model (which assumes the nearest station has a probability of one), indicating that their incorporation into passenger demand forecasting methods has the potential to significantly improve model predictive performance.     

Spatiotemporal traffic forecasting: review and proposed directions

This paper systematically reviews studies that forecast short-term traffic conditions using spatial dependence between links. We extract and synthesise 130 research papers, considering two perspectives: (1) methodological framework and (2) methods for capturing spatial information. Spatial information boosts the accuracy of prediction, particularly in congested traffic regimes and for longer horizons. Machine learning methods, which have attracted more attention in recent years, outperform the naïve statistical methods such as historical average and exponential smoothing. However, there is no guarantee of superiority when machine learning methods are compared with advanced statistical methods such as spatiotemporal autoregressive integrated moving average. As for the spatial dependency detection, a large gulf exists between the realistic spatial dependence of traffic links on a real network and the studied networks as follows: (1) studies capture spatial dependency of either adjacent or distant upstream and downstream links with the study link, (2) the spatially relevant links are selected either by prejudgment or by correlation-coefficient analysis, and (3) studies develop forecasting methods in a corridor test sample, where all links are connected sequentially together, assume a similarity between the behaviour of both parallel and adjacent links, and overlook the competitive nature of traffic links.