交通流驱动的含权网络

文章对含权复杂网络研究的最近进展给予了评述,特别报道了文章作者最近提出的一个交通流驱动的含权技术网络模型.这一模型能够同时给出网络连接度分布的幂函数律、网络强度分布的幂函数律、网络权重分布的幂函数律,以及高聚集性和非相称混合性等五大特征,因此成功地刻画了真实技术网络的无尺度性质和小世界效应.     

交通流驱动的含权网络

文章对含权复杂网络研究的最近进展给予了评述，特别报道了文章作者最近提出的一个交通流驱动的含权技术网络模型。这一模型能够同时给出网络连接度分布的幂函数律、网络强度分布的幂函数律、网络权重分布的幂函数律，以及高聚集性和非相称混合性等五大特征，因此成功地刻画了真实技术网络的无尺度性质和小世界效应     

Routing strategies in traffic network and phase transition in network traffic flow

The dynamics of information traffic over scale-free networks has been investigated systematically. A series of routing strategies of data packets have been proposed, including the local routing strategy, the next-nearest-neighbour routing strategy, and the mixed routing strategy based on local static and dynamic information. The capacity of the network can be quantified by the phase transition from free flow state to congestion state. The optimal parameter values of each model leading to the highest efficiency of scale-free networked traffic systems have been found. Moreover, we have found hysteretic loop in networked traffic systems with finite packets delivering ability. Such hysteretic loop indicates the existence of the bi-stable state in the traffic dynamics over scale-free networks.      

基于复杂网络理论的多元混合空管技术保障系统网络特征分析

为提高空管技术保障系统应对突发事件的能力,本文以空管技术保障系统导航、通信、监视设备覆盖的航路结构为基础,构建系统对应的空间网络模型.提出从灵活性、鲁棒性、高效性三个方面度量空管技术保障系统网络特性,对北京、上海、广州、昆明、沈阳、兰州飞行情报区的空管技术保障系统网络的平均度、度分布、度-度相关性、聚集系数、平均路径长度、直径等进行分析.分析结果显示,各飞行情报区空管技术保障系统的平均聚集系数在0.25—0.39之间,网络聚集程度偏低;网络平均路径长度为3.4,表现出小世界网络特征;度值3时服从幂律分布,度-度分布不表现出正相关或负相关.对网络进行基于度优先的和随机的抗毁性测度,空管技术保障系统网络抗毁性较差,网络的可靠性由少数核心节点决定,应对核心节点进行目标免疫,提高网络的抗毁性.这些规律为空管技术保障系统能力提升、新建扩建提供理论依据,对降低突发事件对空管系统保障能力的影响,保障空中交通持续安全具有现实意义.     

基于复杂网络的交通拥堵与传播动力学分析

本文运用改进的中观交通流模型,研究了网络拓扑结构对交通拥堵的影响,进而分析复杂网络上的交通传播动力学特征和传播规律.结论有助于提出消除交通拥堵的有效控制策略以及交通规划的合理方案. 关键词： 复杂网络 交通流 交通拥堵 传播特性     

Fluctuations and pseudo long range dependence in network flows: A non-stationary Poisson process model

In the study of complex networks (systems), the scaling phenomenon of flow fluctuations refers to a certain power-law between the mean flux (activity) < F_i> of the i-th node and its variance σ_i as F_{i ∝ <Fi^α. Such scaling laws are found to be prevalent both in natural and man-made network systems, but the understanding of their origins still remains limited. This paper proposes a non-stationary Poisson process model to give an analytical explanation of the non-universal scaling phenomenon: the exponent α varies between 1/2 and 1 depending on the size of sampling time window and the relative strength of the external/internal driven forces of the systems. The crossover behaviour and the relation of fluctuation scaling with pseudo long range dependence are also accounted for by the model. Numerical experiments show that the proposed model can recover the multi-scaling phenomenon.}     

基于感知流量算法的复杂网络拥塞问题研究

研究了在具有感知流量的路由策略下,复杂网络的拓扑结构对网络中传输流量的影响.为了描述数据包传输过程的有效性,通过引入一个状态参数,利用由稳态到拥塞的指标流量相变值来刻画网络的吞吐量.基于每个节点的数据包处理能力与该节点的度或介数成比例提出两种模型并进行仿真.仿真结果表明,平均度相同的情况下,模型Ⅰ中,WS小世界网络比ER随机网络和BA无标度网络更容易产生拥塞;模型Ⅱ中,所有网络容量都得到较大的提高,尤其是WS小世界网络.但当网络的基本连接参数改变时,哪种模型更利于网络的流量传输,还要依据网络本身的结构特性 关键词： 复杂网络 无标度网络 感知流量 拥塞     

网络交通流动态演化的混沌现象及其控制

本文以含2条平行路径的交通网络为例, 探讨了网络交通流逐日动态演化问题. 首先, 建立了动态系统模型来刻画网络交通流的演化过程, 动态系统模型的不动点就是随机用户平衡解, 证明了平衡解存在且唯一. 然后, 根据非线性动力学理论, 推导出了网络交通流演化的稳定性条件. 其次, 通过数值实验, 分析了网络交通流的演化特征, 发现了在一定条件下流量的周期振荡和混沌现象. 最后, 以OD需求为控制变量推导出了网络交通流混沌控制的方法.     

Bounded Fluctuations and Translation Symmetry Breaking: A Solvable Model

The variance of the particle number (equivalently the total charge) in a domain of length of a one-component plasma (OCP) on a cylinder of circumference W at the reciprocal temperature =2, is shown to remain bounded as . This exactly solvable system with average density has a density profile which is periodic with period (W)^–1 along the axis of the infinitely long cylinder. This illustrates the connection between bounded variance and periodicity in (quasi) one-dimensional systems.⁽¹⁾ When W the system approaches the two-dimensional OCP and the variance in a domain grows like its perimeter ||. In this limit, the system is translation invariant with rapid decay of correlations.     

Fluctuations in reaction-diffusion systems: A new exactly soluble growth model

The method of compounding moments devised by Van Kampen is used to study the spatial fluctuations in a model describing the irreversible formation of clusters. The reaction and diffusion constants in this model are chosenindependent of the cluster sizes. For a monodisperse initial distribution explicit expressions are calculated for the equal-time and two-time correlation functions of the concentrations ofm- andn-mers. For general initial conditions the fluctuations in the mass density are considered and a scaling theory is presented for the fluctuations at large times. Extensions to more general models are discussed.     

Empirical analysis of a scale-free railway network in China

We present a detailed, empirical analysis of the statistical properties of the China Railway Network (CRN) consisting of 3915 nodes (train stations) and 22 259 edges (railways). Based on this, CRN displays two explicit features already observed in numerous real-world and artificial networks. One feature, the small-world property, has the fingerprint of a small characteristic shortest-path length, 3.5, accompanied by a high degree of clustering, 0.835. Another feature is characterized by the scale-free distributions of both degrees and weighted degrees, namely strengths. Correlations between strength and degree, degree and degree, and clustering coefficient and degree have been studied and the forms of such behaviors have been identified. In addition, we investigate distributions of clustering coefficients, topological distances, and spatial distances.     

A network analysis of the Chinese stock market

In many practical important cases, a massive dataset can be represented as a very large network with certain attributes associated with its vertices and edges. Stock markets generate huge amounts of data, which can be use for constructing the network reflecting the market’s behavior. In this paper, we use a threshold method to construct China’s stock correlation network and then study the network’s structural properties and topological stability. We conduct a statistical analysis of this network and show that it follows a power-law model. We also detect components, cliques and independent sets in this network. These analyses allows one to apply a new data mining technique of classifying financial instruments based on stock price data, which provides a deeper insight into the internal structure of the stock market. Moreover, we test the topological stability of this network and find that it displays a topological robustness against random vertex failures, but it is also fragile to intentional attacks. Such a network stability property would be also useful for portfolio investment and risk management.     

Vehicular motion in 2D city traffic network with signals controlled by phase shift

We study the dynamic behavior of vehicular traffic through the series of traffic lights controlled by phase shift in two-dimensional (2D) city traffic network. The nonlinear-map model is presented for the vehicular traffic. The city traffic network is made of one-way perpendicular streets arranged in a square lattice with traffic signals where vertical streets are oriented upwards and horizontal streets are oriented rightwards. There are two traffic lights for the movement to north or that to east at each crossing. The traffic lights are controlled by the cycle time, split, and phase shift. The vehicle moves through the series of signals on a path selected by the driver. The city traffic with a heterogeneous density distribution is also studied. The dependence of the arrival time on cycle time, split, phase shift, selected path, and density is clarified for 2D city traffic. It is shown that the vehicular traffic is efficiently controlled by the phase shift.     

Lagrangian Velocity Fluctuations in Fully Developed Turbulence: Scaling, Intermittency, and Dynamics

New aspects of turbulence are uncovered if one considers the flow motion from the perspective of a fluid particle (known as the Lagrangian approach) rather than in terms of a velocity field (the Eulerian viewpoint). Using a new experimental technique, based on the scattering of ultrasound, we have obtained a direct measurement of particle velocities, resolved at all scales, in a fully turbulent flow. We find that the Lagrangian velocity autocorrelation function and the Lagrangian time spectrum are in agreement with the Kolmogorov K41 phenomenology. Intermittency corrections are observed and we give a measurement of the Lagrangian structure function exponents. They are more intermittent than the corresponding Eulerian exponents. We also propose a novel analysis of intermittency in turbulence: our measurement enables us to study it from a dynamical point of view. We thus analyze the Lagrangian velocity fluctuations in the framework of random walks. We find experimentally that the elementary steps in the walk have random uncorrelated directions but a magnitude that displays extremely long-range correlations in time. Theoretically, we study a Langevin equation that incorporates these features and we show that the resulting dynamics accounts for the observed one-point and two-point statistical properties of the Lagrangian velocity fluctuations. Our approach connects the intermittent statistical nature of turbulence to the dynamics of the flow.     

Fluctuation scaling in complex systems: Taylor's law and beyond1

Complex systems consist of many interacting elements which participate in some dynamical process. The activity of various elements is often different and the fluctuation in the activity of an element grows monotonically with the average activity. This relationship is often of the form ‘fluctuations ≈ constant × average^α’, where the exponent α is predominantly in the range [1/2, 1]. This power law has been observed in a very wide range of disciplines, ranging from population dynamics through the Internet to the stock market and it is often treated under the names Taylor's law or fluctuation scaling. This review attempts to show how general the above scaling relationship is by surveying the literature, as well as by reporting some new empirical data and model calculations. We also show some basic principles that can underlie the generality of the phenomenon. This is followed by a mean-field framework based on sums of random variables. In this context the emergence of fluctuation scaling is equivalent to some corresponding limit theorems. In certain physical systems fluctuation scaling can be related to finite size scaling.     

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利用HL-2A装置实验数据,初步建立了面向ITERL DB2.0版本的能量约束数据库,采用了统计分析系统(SAS)对HL-2A约束数据进行了分析和评估,开展了能量约束时间对密度的定标律研究,并得到了初步结果。最后通过与ITER定标律和原ASDEX数据的比较,对HL-2A装置上L-模约束品质和欧姆加热条件下斯必泽电阻率对温度的依赖关系进行了讨论。     

SAS系统在HL-2A能量约束数据分析中的应用

利用HL-2A装置实验数据,初步建立了面向ITERL DB2.0版本的能量约束数据库,采用了统计分析系统(SAS)对HL-2A约束数据进行了分析和评估,开展了能量约束时间对密度的定标律研究,并得到了初步结果。最后通过与ITER定标律和原ASDEX数据的比较,对HL-2A装置上L-模约束品质和欧姆加热条件下斯必泽电阻率对温度的依赖关系进行了讨论。     

Intercity express bus flow in Korea and its network analysis

We investigated the express bus flow in Korea and its network topology. By using a gravity type model, we found that the bus flow between cities depends on the square root of the product of the population size of city A and the population size of city B. On the other hand, the total bus flow of a city depends on only its population size. These different dependences on population originate from the network property of the express bus network.     

Benford analysis of quantum critical phenomena: First digit provides high finite-size scaling exponent while first two and further are not much better

Benford's law is an empirical edict stating that the lower digits appear more often than higher ones as the first few significant digits in statistics of natural phenomena and mathematical tables. A marked proportion of such analyses is restricted to the first significant digit. We employ violation of Benford's law, up to the first four significant digits, for investigating magnetization and correlation data of paradigmatic quantum many-body systems to detect cooperative phenomena, focusing on the finite-size scaling exponents thereof. We find that for the transverse field quantum XY model, behavior of the very first significant digit of an observable, at an arbitrary point of the parameter space, is enough to capture the quantum phase transition in the model with a relatively high scaling exponent. A higher number of significant digits do not provide an appreciable further advantage, in particular, in terms of an increase in scaling exponents. Since the first significant digit of a physical quantity is relatively simple to obtain in experiments, the results have potential implications for laboratory observations in noisy environments.