一类有竞争的物流配送中心选址模型

对已有多个配送中心存在的前提出，新增配送中心为获取最大市场占有量如何进行有效的选址决策问题进行了研究，建立了一个选址决策模型，把求解的问题归结为无约束的非线性规划问题，并给出了迭代算法，最后对如何解决考虑多种选址影响因素及多个新增配送中心的复杂情况进行了讨论。     

基于MQ插值的变形网格在船舶阻力预报中的应用

在非结构切分网格的框架下,发展了一种基于Multi-Quadric插值的变形网格技术,结合CFD软件STAR-CCM+,采用SST湍流模型,并以VOF法进行自由液面的追踪,将该变形网格技术应用于带附体穿浪双体船的阻力预报中。分别以网格的拉伸变形和斜率变形实现了阻流板和尾楔的边界运动,计算了阻流板高度为4 mm、6 mm和8 mm以及尾楔角度为5°、10°和15°时的工况。计算结果表明,变形网格方法与固定网格方法取得了相同的精度;同试验值相比,在不同工况下变形网格最大平均误差约为6.67%,验证了其可行性。但是,相比于固定网格方法,变形网格方法的计算时耗最大可减少40%,因此采用该变形网格方法可极大地提高带可变形附体的船舶的阻力预报效率。     

基于三维势流理论的耐波性数值预报

准确预报船体运动响应对于砰击等波浪载荷的计算以及合理结构设计具有重要意义。船舶在大幅波浪中的运动呈明显的非线性,而现阶段耐波性预报多采用线性切片方法。三维水动力分析软件 WASIM基于时域势流理论,采用 Rankine面元法预报船舶在波浪中的运动响应,并考虑了多种非线性因素。本文以标模 DTMB5512为对象,采用 WASIM预报其在不同航速下的耐波性,并与基于线性切片理论的计算结果和模型试验结果进行对比。结果表明：利用 WASIM计算得到的船体运动响应比其他方法更接近试验值,合理体现了船舶在风浪中的实际耐波性能。因此,利用 WASIM能够较好地评估船舶在波浪中的非线性耐波特性。     

The relationship between urban street networks and private motorized trips at the city level

There are factors that impact car usage in urban areas, such as density, diversity and design, but there have been few studies that examine the relationship between street network factors and car usage at the city level (macro level). This paper focuses on this relationship by introducing urban street network variables, such as blocks per area, nodes per block and length of roads and motorways, as independent variables and the percentage of daily trips by private motorized modes as the dependent variable. The street network in this study includes interconnecting lines and points that present streets, roads, motorways, intersections and blocks. The strength of the relationship in this study is found using multiple linear regression. The findings of this research indicate that an increase in car usage is correlated with an increasing number of blocks per area, number of nodes per block and length of motorways. In addition, because the urban street network is the result of macro-scale planning decisions, considering this relationship can lead to better planning decisions.     

低压气液混输采气管道串接集气模式研究

针对杭锦旗气田高液气比气井井间串接集气距离长、管道压损大的问题,文中用权重法估算了影响管道气液混输距离的因素,表明管道直径是影响集气距离的最重要因素,权重比约56.1%。根据杭锦旗气田气井生产参数,对不同采气管道规格串接模式进行了研究,确定了适用于不同集气量和串接井数的采气管道规格系列,提出了直线式与辐射式相结合的井间串接模式,为杭锦旗气田地面集输站场和管网设计提供技术依据。     

Short‐term traffic flow prediction with linear conditional Gaussian Bayesian network

Traffic flow prediction is an essential part of intelligent transportation systems (ITS). Most of the previous traffic flow prediction work treated traffic flow as a time series process only, ignoring the spatial relationship from the upstream flows or the correlation with other traffic attributes like speed and density. In this paper, we utilize a linear conditional Gaussian (LCG) Bayesian network (BN) model to consider both spatial and temporal dimensions of traffic as well as speed information for short‐term traffic flow prediction. The LCG BN allows both continuous and discrete variables, which enables the consideration of categorical variables in traffic flow prediction. A microscopic traffic simulation dataset is used to test the performance of the proposed model compared to other popular approaches under different predicting time intervals. In addition, the authors investigate the importance of spatial data and speed data in flow prediction by comparing models with different levels of information. The results indicate that the prediction accuracy will increase significantly when both spatial data and speed data are included. Copyright © 2016 John Wiley & Sons, Ltd.     

Mathematical model for optimising the sequence for clearing snow from the manoeuvring area during winter operations

This article considers the optimisation of the sequence for clearing snow from stretches of the manoeuvring area of an airport. This issue involves the optimisation of limited resources to remove snow from taxiways and runways thereby leaving them in an acceptable condition for operating aircraft. The airfield is divided into subsets of significant stretches for the purpose of operations and target times are established during which these are open to aircraft traffic. The document contains several mathematical models each with different functions, such as the end time of the process, the sum of the end times of each stretch and gap between the estimated and the real end times. During this process, we introduce different operating restrictions on partial fulfilment of the operational targets as applied to zones of special interest, or relating to the operation of the snow‐clearing machines. The problem is solved by optimisation based on linear programming. The article gives the results of the computational tests carried out on five distinct models of the manoeuvring area, which cover increasingly complex situations and larger areas. The mathematical model is particularised for the case of the manoeuvring area of Adolfo Suarez Madrid—Barajas Airport. Copyright © 2016 John Wiley & Sons, Ltd.

Highlights
• Optimal sequence for clearing snow from the manoeuvring area of an airport.
• Contains optimising algorithms solved using CPLEX LP‐based tree search.
• Restrictions on partial fulfilment of operational targets applied to subsets of significant stretches, used for planning the operation of snow‐clearing machines.
• Model applied to the case of the manoeuvring area of Adolfo Suárez Madrid Barajas Airport.
• Conclusions are given on the results of the computational tests carried out. There are five models of the manoeuvring area which cover increasingly complex situations and larger areas.

     

基于HALCON的视频交通参数检测方法

基于图像处理软件HALCON对视频交通参数检测方法进行讨论,研究双线性插值的图像距离标定方法和基于灰度统计的交通参数检测算法及流程,选取具有代表性的北京五道口交叉路口及成府路路段监控视频进行试验,证明方法的有效性,对试验结果中车速误差及混合交通启动车头时距规律进行深入分析,提出误差改进措施,并将混合交通排队车流启动车头时距规律与美国交通工程手册中车头时距规律进行对比分析。     

基于秩约束的车辆遮挡点恢复方法

为了恢复车辆跟踪过程中丢失的特征点,提出了一种基于秩约束的车辆遮挡点恢复方法,该方法利用所有车辆图像点组成一个秩3的矩阵,并利用该特性构造一个投影矩阵,利用该投影矩阵求到车辆遮挡点,再将求到的车辆遮挡点代替图像中的车辆遮挡点,经过多次迭代,最后求到车辆遮挡点的真实位置。该方法的优点是所有的图像及图像点都平等地看待,模拟试验和真实试验表明,该方法具有鲁棒性好、收敛性好及误差小等优点。     

不等时距GM(1,1)模型预测地基沉降研究

分别采用直线插值、三次样条插值、BP神经网络3种方法,用M ATLAB语言编制程序将不等时距序列转化为等时距序列,采用灰色理论预测沉降.由于BP神经网络强大的非线性映射功能,可以避免常规插值法所造成的一系列误差.实际工程应用结果表明,利用直线插值、三次样条插值和BP神经网络与灰色理论联合建模所得的预测值与实测值的最大相对误差分别为17.2%,5.9%和4.6%.由此可见BP神经网络和灰色理论联合建立的GM(1,1)模型用于预测路基沉降最为精确.