Maritime network dynamics before and after international events

Investigating the influence of international events on global maritime networks is a challenging task that must comprehensively incorporate geographical, political, and maritime sciences. Understanding global maritime network dynamics is an initial and critical step in this investigation. This study proposes an automatic identification system (AIS)-based approach to understanding maritime network dynamics before and after international events. In this approach, a spatiotemporal modeling method is introduced to measure the similarity in shipping trends before and after international events. Then, a spatiotemporal analytic framework is proposed to understand the maritime network dynamics by grouping similar situation, and assessing possible indirect effects within a network. Finally, three case studies of international events, military conflict, lifted economic sanctions, and government elections, were used to investigate the observed network dynamics possibly affected by international events. The results indicate that container, tanker, and bulk shipping between India and its connected countries all declined more than 69% after military conflicts between India and Pakistan in August 2015. Tanker shipping between Iran and the United Arab Emirates increased 51% after economic sanctions on Iran were lifted. Container shipping between Sri Lanka and Singapore, Malaysia, and India increased more than 74% after the general election in Sri Lanka. These investigations demonstrate the feasibility of the proposed approach in assessing the possible effects of international events on maritime network dynamics.     

Development history and accessibility evolution of land transportation network in Beijing-Tianjin-Hebei region over the past century

From the development of modern transportation to the current era of high-speed transportation networks, the Beijing-Tianjin-Hebei (BTH) region has always played a national leading role in land transportation development of China. In order to explore the long-term evolutionary characteristics of land transportation in the BTH region, this paper utilized a temporal scale of 100 years to systematically interpret the development process of the land transportation network. Taking 13 cities within the BTH region as research anchor cities, we took into account “leaping” mode of transportation in order to investigate the evolution of accessibility. Our research shows the following results: (1) The land transportation network in the BTH region has undergone five stages of development: the initial period of modernization (1881–1937); the period of stagnation of transportation development (1937–1949); the network expansion period (1949–1980); the period of trunk construction (1980–1995), and the period of high-speed transportation network development (1995–present). The network structure centered around Beijing has existed from the outset of modern transportation development. (2) The accessibility spatial pattern of land transportation in BTH region has evolved from expansion along traffic corridors to the formation of concentric circles. The stratified circular structure of transportation in anchor cities has gradually developed into a contiguous development pattern. (3) There are clear hierarchical differences in the transportation structures of anchor cities. Beijing has always been at the top of this hierarchy, while the hierarchical position of Zhangjiakou has fallen noticeably since 1949. The Beijing-Tianjin region was the first region to form a short-duration transportation circle structure, while the transportation advantages of the central part of Hebei Province, which is located in the center of the BTH transportation region, have yet to be realized.     

云雷达和微波辐射计联合反演大气湿度廓线的初步研究

利用中国气象局大气探测试验基地的微波辐射计亮温值、对应的云雷达测得的反射率因子和L波段探空数据,采用BP(back propagation)神经网络作为反演工具,反演得到大气垂直湿度廓线。将天气情况分为晴天、低云、中云和高云四种情况,对比不加入反射率因子的反演湿度廓线,分析两种反演方法在各高度层的均方根误差。对比结果表明,加入反射率因子的反演湿度廓线与探空廓线的相关系数平均值为0.862,均方根误差为14. 9%,而不添加反射率因子的相关系数平均值为0.763,均方根误差为19.2%。     

追踪比特币新币走向:一种基于交易网络结构特征识别矿工的方案

比特币是近年关注度最高的虚拟电子货币,"挖矿"是在此生态中最重要的获利方式之一.本文通过分析比特币交易间的引用关系,追踪区块链中挖矿所得的新币走向,构建新币流通网络.通过对比不同矿池所挖得的新币流通网络,设计了启发式算法识别比特币矿工群体,并以此推断矿池常见的收益分配方式.此外,本文还对矿工群体规模的逐年增长趋势进行了刻画.     

基于Quanser实验平台的带有输出约束单连杆柔性机械臂的神经网络控制

机械臂在航空航天、服务等领域的应用越来越广泛,其研究也越来越深入.相比于刚性机械臂,柔性机械臂质量轻、能耗小,具有更好的性能.但是,由于柔性机械臂本身的结构与材料具有特殊性,其在运动过程中会产生弹性形变与振动,这就给机械臂的定位、轨迹跟踪带来了困难,因此对其振动抑制的研究具有重要意义.本文利用假设模态法对单连杆柔性机械臂系统进行建模,通过李雅普诺夫直接法实现了闭环系统的稳定性.由于一些实际问题对控制系统的状态量有特殊要求,因此采用正切函数形式的障碍李雅普诺夫策略来处理输出约束问题,之后利用神经网络控制方法来逼近系统的不确定性,通过李雅普诺夫法对闭环系统的稳定性进行了分析,并基于Matlab平台设计仿真、基于Quanser实验平台进行实验,对控制器的控制性能进行了验证.     

欺骗攻击环境下带有传感器故障的大规模电网分布式状态估计

本文研究了欺骗攻击环境下带有传感器故障的大规模电网分布式状态估计问题.通过引入拓扑关系来描述分布式传感器节点之间的相互关系,使用随机Bernoulli序列描述欺骗攻击模型及其随机特性.基于Lyapunov方法证明了带有传感器故障的系统在遭受欺骗攻击环境下的均方稳定及H_∞稳定的充分条件,并基于LMI设计了满足H_∞性能指标的分布式状态估计器.最后通过数值仿真验证了所设计估计器的有效性.     

关于带有协作/竞争机制时变积分器网络一致性的收敛速率

本文探讨了时变无向网络达到状态一致过程中的收敛速率问题.首先基于一般的时变无向网络展开研究,证明了其收敛速率随耦合权重的增加而提高.同时,给出了收敛速率的明确下界,并指出这个下界是耦合权重的线性函数.基于这些结论,本文研究了带符号网络的收敛速率问题,发现只要带有正权值的边具有（δ,T）连通性,就可以增大这些边的权重而保持其余边（带有负权值）不变,使一致性以指数的速率达到.本文的证明过程主要基于完全一致可观这一概念.另外,本文也得到了这样的结论：一致性误差值可以从系统一段时间内的相对状态值中重建.这对于分布式网络中滤波器的状态估计有一定的借鉴意义.     

中国城市网络化空间联系结构——基于银行网点数据的研究

基于当前城市网络和金融地理研究,以全国336个地级以上行政单元(城市)为研究对象,以33家国内外银行的88022个网点各城市间的级别和数量分布为基础数据,运用链锁模型、Zipf法则、社会网络分析等研究方法,对中国市间联系和城市节点的结构特征进行分析。研究表明：京津冀、长三角、珠三角、成渝和长江中游等五大城镇密集区之间的联系成为这一网络的主干,东西部网络密度以胡焕庸线为界呈现明显差异;城市联通度的规模分布符合Zipf法则,但呈现明显的双分形特征,各城市的节点度同样以胡焕庸线为界在东西部呈现显著差异;此外,国有银行、股份制银行和外资银行所分别对应的城市整体联通度和相对联通度在空间分布上也存在明显差别;上述结构特征同各城市经济规模和人口规模之间存在较强的相关性。从形成机制上看,朝向集中化和均衡化的一般空间政策和行业空间政策对这一网络格局的形成具有深刻影响。     

基于网络分析的城市影响区和城市群空间范围识别

以不打破行政界线为前提,利用Huff模型,基于矢量数据,采用最短交通路网距离和城市综合规模值来综合测算腹地与中心城市之间的势能,根据势能确定腹地县域的归属,对全国地级及以上城市的空间影响范围进行识别,并和基于改进场强模型的城市影响腹地范围界定结果进行对比。以全国发育较成熟的15个城市群为对象,综合测定城市群的影响范围,并与城市群规划中的空间范围进行对比,提出城市群空间范围调整建议。并以长株潭城市群为例,通过社会网络分析方法,综合分析测定城市群的空间影响范围。研究结果可为城市(群)规划提供科学依据和方法参考。     

A linear tessellation model to identify spatial pattern in urban street networks

Street patterns reflect the distribution characteristics of a street network and affect the urban structure and human behavior. The recognition of street patterns has been a topic of interest for decades. In this study, a linear tessellation model is proposed to identify the spatial patterns in street networks. The street segments are broken into consecutive linear units with equal length. We define five focal operations using neighborhood analysis to extract the geometric and topological characteristics of each linear unit for the purpose of grid-pattern recognition. These are then classified by Support Vector Machine, and the result is optimized based on Gestalt principles. The experimental results demonstrate that our method is effective for mining grid patterns in a street network.