Vulnerability analysis for large-scale and congested road networks with demand uncertainty

To assess the vulnerability of congested road networks, the commonly used full network scan approach is to evaluate all possible scenarios of link closure using a form of traffic assignment. This approach can be computationally burdensome and may not be viable for identifying the most critical links in large-scale networks. In this study, an “impact area” vulnerability analysis approach is proposed to evaluate the consequences of a link closure within its impact area instead of the whole network. The proposed approach can significantly reduce the search space for determining the most critical links in large-scale networks. In addition, a new vulnerability index is introduced to examine properly the consequences of a link closure. The effects of demand uncertainty and heterogeneous travellers’ risk-taking behaviour are explicitly considered. Numerical results for two different road networks show that in practice the proposed approach is more efficient than traditional full scan approach for identifying the same set of critical links. Numerical results also demonstrate that both stochastic demand and travellers’ risk-taking behaviour have significant impacts on network vulnerability analysis, especially under high network congestion and large demand variations. Ignoring their impacts can underestimate the consequences of link closures and misidentify the most critical links.     

基于BP人工神经网络的滑坡预测分析

文章以汶川地震引发的滑坡为研究对象,以震中距、地震烈度、坡度、前缘高程、坡高和岩性等影响坡体稳定性的因素为切入点,利用BP人工神经网络对实际坡体的稳定性进行了预测分析。结果表明,BP人工神经网络方法能有效预测坡体的稳定情况。     

船舶混合动力技术发展趋势分析

通过近年发布的《国际海事组织海运温室气体减排初步战略》等相关减排措施,提出船舶混合动力技术作为优选解决方式。介绍该技术发展背景,阐述其定义、架构及国内外发展应用现状,分析油电混合动力技术、气电混合动力技术的特点,对船舶混合动力技术发展趋势及应用前景进行展望,经调查研究,船舶混合动力推进系统具有操纵性好、效率高及特定工况排放低等特性,减排优势明显。     

船舶电子证书应用及监管思考

对于如何保证船舶证书和技术文件的完整可查,提出相应的船舶电子证书应用及监管思考。介绍船舶电子证书可进一步拓宽无纸化办公领域、提高检验过程的便利性、提高港口检查的高效性,并可大幅减少证书制作成本、缩短寄送时间,有效提升工作效率;同时,可促进相关部门船舶智能化管理的优化升级。     

线性绞车电控系统开发与应用

基于广州打捞局120 000 kN抬浮力打捞工程船配套4 500 kN线性绞车的技术要求,提出线性绞车电控系统设计方案。从线性绞车在打捞工程船中的作业工况、电控系统的通讯架构、线性绞车单台控制及远程联动的自动控制、人机界面操作等方面进行研究,介绍线性绞车电控系统的设计思路,为线性绞车在打捞沉船工作中的正确运用提供了理论支撑和技术保障。     

新能源电力推进对比分析

文章基于全球低碳节能政策,研究并概述了直流微网新能源电力推进系统及其关键技术,对比了以太阳能、蓄电池、氢燃料电池等为主动力的电力推进系统,并分析其性能、综合效率及实际船舶应用,对推进绿色船舶、节能减排等具有重要的实际意义。     

Developing an enhanced weight-based topological map-matching algorithm for intelligent transport systems

Map-matching (MM) algorithms integrate positioning data from a Global Positioning System (or a number of other positioning sensors) with a spatial road map with the aim of identifying the road segment on which a user (or a vehicle) is travelling and the location on that segment. Amongst the family of MM algorithms consisting of geometric, topological, probabilistic and advanced, topological MM (tMM) algorithms are relatively simple, easy and quick, enabling them to be implemented in real-time. Therefore, a tMM algorithm is used in many navigation devices manufactured by industry. However, existing tMM algorithms have a number of limitations which affect their performance relative to advanced MM algorithms. This paper demonstrates that it is possible by addressing these issues to significantly improve the performance of a tMM algorithm. This paper describes the development of an enhanced weight-based tMM algorithm in which the weights are determined from real-world field data using an optimisation technique. Two new weights for turn-restriction at junctions and link connectivity are introduced to improve the performance of matching, especially at junctions. A new procedure is developed for the initial map-matching process. Two consistency checks are introduced to minimise mismatches. The enhanced map-matching algorithm was tested using field data from dense urban areas and suburban areas. The algorithm identified 96.8% and 95.93% of the links correctly for positioning data collected in urban areas of central London and Washington, DC, respectively. In case of suburban area, in the west of London, the algorithm succeeded with 96.71% correct link identification with a horizontal accuracy of 9.81 m (2σ). This is superior to most existing topological MM algorithms and has the potential to support the navigation modules of many Intelligent Transport System (ITS) services.     

Using on-board logging devices to study the longer-term impact of an eco-driving course

In this paper the long-term impact of an eco-driving training course is evaluated by monitoring driving behavior and fuel consumption for several months before and after the course. Cars were equipped with an on-board logging device that records the position and speed of the vehicle using GPS tracking as well as real time as electronic engine data extracted from the controller area network. The data includes mileage, number of revolutions per minute, position of the accelerator pedal, and instantaneous fuel consumption. It was gathered over a period of 10 months for 10 drivers during real-life conditions thus enabling an individual drive style analysis. The average fuel consumption four months after the course fell by 5.8%. Most drivers showed an immediate improvement in fuel consumption that was stable over time, but some tended to fall back into their original driving habits.     

一种基于独立成分分析和径向基神经网络的人脸识别新方法

提出了一种新的基于独立成分分析和径向基神经网络的人脸识别方法。独立成分分析可以从高阶上消除特征数据的相关性,改进了主成分分析方法只能从2阶上消除数据相关性的弱点;最终特征数据的分类由RBF神经网络来实现。在人脸数据库上的实验结果表明该新方法的识别性能较其他方法有了很大提高。     

人的可靠性分析方法及其在军事活动中的应用

回顾了人的可靠性分析发展的历史和现状,重点对现在已存在的人的可靠性分析方法进行了介绍分析,提出并简要介绍了两种在军事活动中适用的人的可靠性评估方法的基本原理：基于粗糙集的人的可靠性评估法和基于贝叶斯的人的可靠性评估法,最后分析了人的可靠性研究中存在的问题。