马来西亚东海岸铁路CTCS-2级列控系统方案研究

对马来西亚东海岸铁路CTCS-2级列控系统方案进行了分析和研究;针对单线自动站间闭塞情况提出了CTCS-2级列控系统方案;通过综合比较后提出马来西亚东海岸铁路列控系统推荐方案,可为CTCS-2级列控系统在单线自动站间闭塞中的应用提供一定参考.     

大跨悬索桥MTMD抖振控制的参数优化

针对悬索桥抖振控制问题,建立有限元模型,应用神经网络和遗传算法对多重调频质量阻尼器(MTMD)进行双参数优化。以某大跨悬索桥为例,利用神经网络改进的谐波合成模拟方法(RBF-WAWS法)对脉动风速进行模拟,并换算成抖振力作用主梁上,通过时程分析及后处理获取主跨跨中横桥向响应值。将响应值的均方差作为优化目标函数,以MTMD总质量、个数及阻尼比作为优化变量和约束条件,采用神经网络拟合目标函数并应用改进的自适应遗传算法进行寻优。结果表明,优化后的MTMD能有效控制悬索桥在脉动风作用下的抖振响应,减振率达48%。提出的理论与计算方法对悬索桥中MTMD的设置及参数选取具有实际工程意义。     

涌浪条件下斜坡式防波堤堤脚块石稳定性

海外港口工程大部分位于以涌浪为主的海域,防波堤在涌浪作用下的稳定性尚未得到全面认识。对于斜坡堤,除了护面对其稳定性至关重要外,堤脚对其稳定性也很重要。以某一具体港口防波堤工程为例,通过波浪断面和局部整体物理模型试验,对涌浪作用下斜坡堤堤脚块石的稳定性进行了研究。根据试验结果,对比正向和斜向波浪作用下斜坡堤堤脚块石的稳定性结果,重点分析了斜向波浪作用下斜坡堤堤头圆弧段堤脚块石发生破坏的原因及其随入射波浪周期和水位的变化关系,并对原方案堤脚进行了优化。     

海底混响非瑞利特性研究及神经网络应用

基于单元散射理论介绍了瑞利分布模型和K分布模型,通过计算混响偏度和峰度判断出海底混响偏离瑞利分布模型,并利用CW信号、LFM信号的试验混响数据进行阵元域、波束域上的PDF曲线拟合。结果表明,海底混响的统计特性更趋向于K分布模型。利用BP网络方法和海底混响、点目标仿真信号的PDF特性进行了目标识别验证,其正确识别率达到了92%以上,且计算量大大降低。     

智慧高速公路设计案例分析

本文以某智慧高速的设计案例为依托,首先对国内外智慧高速发展和应用现状进行归纳总结,分析认为电动化、智能化的新型运载工具,信息化和功能专业化的基础设施,开放、共享、协同的管理与服务将是未来高速公路三大发展趋势。通过对高速公路使用者和管理者的需求针对性地精准分析,构建面向高速公路使用者和管理者的创新型应用服务。结合新技术的发展趋势,以服务需求为导向,建设"三网合一"智慧高速基础设施和智慧云控平台构成、数据流为驱动的、"开放、包容、创新"的智慧高速公路。基于案例分析的智慧高速规划设计全过程,对于国内智慧高速的整体设计和建设规划具有重要参考价值,探索开辟全新的高速公路智能化建设方向和思路。     

A latent class accelerated hazard model of social activity duration

Over the past decade, activity scheduling processes have gained increasing attention in the field of transportation research. However, still little is known about the scheduling of social activities even though these activities account for a large and growing portion of trips. This paper contributes to this knowledge. We analyze how the duration of social activities is influenced by social activity characteristics and characteristics of the relationship between the respondent and the contacted person(s). To that end, a latent class accelerated hazard model is estimated, based on social interaction diary data that was collected in the Netherlands in 2008. Chi-square tests and analyses of variance are used to test for significant relations between the latent classes and personal and household characteristics. Findings suggest that the social activity characteristics and the characteristics of the relationship between the socializing persons are highly significant in explaining social activity duration. This shows that social activities should not be considered as a homogenous set of activities and it underlines the importance of including the social context in travel-behavior models. Moreover, the results indicate that there is a substantial amount of latent heterogeneity across the population. Four latent classes are identified, showing different social activity durations, and different effects for both categories of explanatory variables. Latent class membership can be explained by household composition, socio-economic status (education, income and work hours), car ownership and the number of interactions in 2 days.     

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。     

The effectiveness of a European speed limit versus an international bunker-levy to reduce CO2 emissions from container shipping

In the fight to reduce CO₂ emissions from international shipping, a bunker-levy is currently under consideration at the International Maritime Organization (IMO). Faced with the inability of the IMO to reach an agreement in the short term, the European Commission is now contemplating a unilateral measure of a speed limit for all ships entering European Union (EU) ports. This paper argues that this measure is counterproductive for two reasons. Firstly, because it may ultimately generate more emissions and incur a cost per ton of CO₂ which is more than society is willing to pay. Secondly, because it is sub-optimal compared to results obtained if an international bunker-levy was to be implemented. These elements are illustrated using two direct transatlantic services operated in 2010.     

The value of options for time charterparty extension: an artificial neural networks (ANN) approach

The most frequently associated options in the physical shipping market are options to extend the charter period on time charters and additional shipment options on contracts of affreightment. The value of freight options, in practice, is estimated mostly by referring to forward curves. An option on freight has different properties from its financial counterparts, and the straightforward adoption of theoretical models does not produce promising results. In this paper, extension options, which have the property of options on futures, were transformed into regular European options before the application of the Black-Scholes model (BSM). The efficient market hypothesis, which justifies the parity of the performance of a long-term charter to that of repetitive short-term charters, worked as the basis for the transformation. The option values determined by the BSM were compared with actual realized values. Additionally, the artificial neural networks (ANN) was employed to derive the option values. This study is meaningful as the first-time application of both the closed-form solution and the ANN to the valuation of physical freight options. The research results can contribute to the quality of chartering decisions. The results could also be used in quantifying credit risk, as extension options tend to be granted to charterers with more creditability.     

固态胺纤维制备及在密闭舱内吸附CO2性能研究

以聚丙烯腈纤维(PAN)为基体,通过水解、酰氯化及与聚乙烯亚胺(PEI)接枝反应制备得到多胺基型固态胺纤维.应用红外光谱仪、热重分析仪及扫描电子显微镜表征了纤维的官能团结构、热稳定性及表面微观形貌.在温度25.0℃、相对湿度80%、初始CO2浓度1.0%的条件下,测得纤维在30 min内对CO2的吸附量可达154.4 g/kg;105℃ 水蒸气再生10 min,循环吸附再生50次,纤维的再生效率为98.3%.