A methodology for classification by priority for action: Selecting road stretches for network noise action plans

Road traffic noise is an element of outstanding importance within the overall context of environmental impact. This problem must be technically addressed from an efficient viewpoint, and solutions or alternatives should be considered by means of appropriate and consolidated procedures.Up to now, there is no regulated guideline for establishing well-founded priorities when dealing with the diverse road stretches included in the corresponding Action Plans against noise under the Environmental Noise Directive (2002/49/EC). To this end, the present study proposes a methodology to sort, by priority, road stretches identified by their noise problems and therefore requiring appropriate action. The methodology is based on the so-called “road stretch priority index” (henceforth referred to as RSPI). This index involves a number of variables (called “road stretch priority variables”) that are weighted according to their influence on the road traffic noise problem. Thus, the RSPI makes it possible to prioritize different stretches of the Action Plan. To illustrate the application of the proposed methodology, this paper also describes a real case entailing a difficult choice, applying the proposed methodology to a review of the Action Plan against Noise 2008–2012 in the province of Almería, for the road network of the regional government of Andalusia, Spain.     

计算机辅助船舶技术经济论证

本文介绍了 Apollo CAD 工作站上开发的船舶技术经济论证系统,并叙述了船舶技术经济论证的计算方法,文中还详细讨论了在应用计算机条件下本系统所具有的一些特色,如指标与变量关系曲面的构成,多目标优选方案等,最后阐述了本系统的总体结构及运行环境.     

Latent temporal preferences: An application to airline travel

An essential element of demand modeling in the airline industry is the representation of time of day demand—the demand for a given itinerary as a function of its departure or arrival times. It is an important datum that drives successful scheduling and fleet decisions. There are two key components to this problem: the distribution of the time of day demand and how preferred travel time influences itinerary choice. This paper focuses on estimating the time of day distribution. Our objective is to estimate it in a manner that is not confounded with air travel supply; is a function of the characteristics of the traveler, the trip, and the market; and accounts for potential measurement errors in self-reported travel time preferences. We employ a stated preference dataset collected by intercepting people who were booking continental US trips via an internet booking service. Respondents reported preferred travel times as well as choices from a hypothetical set of itineraries. We parameterize the time of day distribution as a mixture of normal distributions (due to the strong peaking nature of travel time preferences) and allow the mixing function to vary by individual characteristics and trip attributes. We estimate the time of day distribution and the itinerary choice model jointly in a manner that accounts for measurement error in the self-reported travel time preferences. We find that the mixture of normal distributions fits the time of day distribution well and is behaviorally intuitive. The strongest covariates of travel time preferences are party size and time zone change. The methodology employed to treat self-reported travel time preferences as potentially having error contributes to the broader transportation time of day demand literature, which either assumes that the desired travel times are known with certainty or that they are unknown. We find that the error in self-reported travel time preferences is statistically significant and impacts the inferred time of day demand distribution.     

基于场变量的公路边坡稳定分析

利用 ABAQUS 中场变量对时间增量步控制的优势,提出了一种公路边坡稳定性分析新方法-基于场变量的强度折减法。对该方法应用于公路边坡稳定性分析的可行性进行验证,并与极限平衡法以及二分法计算得出的最小安全系数进行比较,分析其相对误差。结果表明：该方法用于公路边坡稳定性分析是有效、可靠的,提高了计算效率,对于公路工程边坡稳定性分析具有重要意义。     

Hilbert空间映射下非线性分类的变元可分离核函数

分析变元可分离函数K（u,v）=k（u）k（v）成为核函数对非线性支持向量分类机的作用,由新方法构造的非线性支持向量分类机可以使相应的算法得以简化.     

线程同步中的条件变量控制应用

针对多线程并发中的竞争和协作控制问题,介绍了Linux环境下的条件变量机制及其相关系统调用,并对其工作原理进行分析.以线程同步中的司机、售票员模型为例,指出一般信号量解决方案的不足,提出基于条件变量机制的解决方案,并给出一个具体的控制模型.     

基于变点分析思想的高维机械噪声数据本征维估计方法

利用变点分析思想,针对高维数据协方差矩阵的特征值曲线特点,提出一种本征维估计方法:基于均值估计的特征值变点法,并应用于某双层圆柱壳体的机械噪声数据处理中。通过与其他现有常用方法的比较分析,验证了基于均值估计特征值变点法的可行性。结果显示:基于均值估计的特征值变点法理论简单、计算简便,计算结果客观、合理,对某双层圆柱壳体机械噪声数据的处理效果较好。     

多变量聚类分析的高速公路交通流状态实时评估

针对交通状态单变量判断传统方法的不足,本文建立了基于多变量聚类分析的高速公路交通流状态实时评估方法.结合实际交通流数据,利用模糊聚类、K均值聚类等算法对速度、流量等向量进行聚类分析,给出适合当前高速公路特点的交通状况划分方法和关键参数.本文方法能够实时、准确、全面地反映交通流的运行情况,为制定高效的交通管理控制方案及合理的出行方案提供数据基础.     

基于集成模型的多维活动-出行决策研究

对个体活动-出行行为的5个决策维度进行联合建模分析,包括连续型的通勤距离、离散型的日通勤出行方式和通勤出发时间、小汽车拥有和日非工作活动量.一方面,作为内生变量,这5个决策维度受到个体性别、收入、教育水平等社会经济属性影响;另一方面,它们之间的相互影响关系也通过可见的结构关系及不可见的相关关系得到证实.比如,通勤出行距离越长,出行者家庭小汽车的拥有量越大;通勤出行距离、公交出行方式的选择均对日非工作活动量有负面影响;当通勤者家庭拥有更多的小汽车或者通勤出行距离很长时,他们选择小汽车和公交车的概率更高.本文证实了个体活动-出行决策维度之间的复杂作用关系,证实了对多维活动-出行决策进行综合集成分析的重要性.     

中国经济增长的波动分析

对国民经济增长的波动进行计算分析。应用Mexican Hat小波对国内生产总值（GDP）的增长率进行多时间尺度分析，再利用宏观经济学的理论从政府宏观调控政策、投资、消费等方面分析引起波动的原因。在不同时间尺度下，经济波动受到政策、投资和消费及重大政治事件的影响。通过对经济增长波动的因素及规律的分析，可以提高对经济发展的预见性，促进经济更好的增长。