基于“小世界”网络模型的产业集群内企业竞争优势仿真分析

将产业集群作为一种知识的综合体,由于产业集群知识网络的系统特征是和复杂网络同质的,而“小世界”网络具有复杂网络良好的关联结构,基于“小世界”网络模型,建立以产业集群小世界网络为基础的知识转化效益转移收益分析模型,同时开展深入的数据模拟解析工作,研究发现:只要在产业集群发展初期适当控制企业间网络规模和临近性,随着产业集群知识网络中企业成员交流频率的提高,企业聚集度的增加,企业的知识转移效率与能力都会得到更高的提升,从而最终提高由知识转移创新收益所带来的集群企业竞争优势。

基于网络环境的科技产业知识生产行为研究

本文模型化了一个局部区域网络中知识生产组织的知识生产行为,选择在多变的和动态的任务环境下产业是否进入分析某领域进行知识生产或如何进行知识生产。考察了"小世界"网络在吸引其他组织形成区域产业集群的特性、作用和如何加强知识创新的效率。研究结果表明,在一个地理空间范围内,一个具有良好特性的网络结构能够导致大量的知识产出,而且也能够加速区域生产经济的发展。

多中心星型网络上动力系统的混沌同步

提出一类多中心星型网络模型,通过其拓扑性质的分析,表明它是一类更好的小世界网络,给出该网络上的一个巨型动力系统达到混沌同步的解析条件。

二部图在用户-网站中的实证研究

通过分析用户浏览网站的访问日志,建立用户-网站的二部图。其次分别通过对用户和网站进行投影,构建出用户网和网站网。然后通过计算节点间的相似度来确定边的权值。最后计算了用户网和网站网进行了度分布、平均最短路径、平均群聚系数、点强度等拓扑参数以及时间间隔分布等人类动力学特性。证实了该网络是无标度网络,且具有"小世界"效应特性。

Structures of semantic networks: how do we learn semantic knowledge

Global semantic structures of two large semantic networks, HowNet and WordNet, are analyzed. It is found that they are both complex networks with features of small-world and scale-free, but with special properties. Exponents of power law degree distribution of these two networks are between 1.0 and 2. 0, different from most scale-free networks which have exponents near 3.0. Coefficients of degree correlation are lower than 0, similar to biological networks. The BA （Barabasi-Albert） model and other similar models cannot explain their dynamics. Relations between clustering coefficient and node degree obey scaling law, which suggests that there exist self-similar hierarchical structures in networks. The results suggest that structures of semantic networks are influenced by the ways we learn semantic knowledge such as aggregation and metaphor.

连接分形的城市

和所有生命系统一样,有活力的城市本质上都具有分形特征。汽车和人口增长带来的压力迫使20世纪的城市规划者推行反分形的几何类型,传统城市的分形特征被去除,给城市肌理造成灾难性的影响。要消除这种破坏,必须深入细致地理解一些问题:(1)分形特征都有哪些;(2)有活力的城市肌理中错综复杂的相互连接;(3)连接和修补城市空间的方法;(4)整合行人、汽车和公共交通的有效方式;(5)如何将实体联系与电子联系结合起来。首先,我们应该消除对分形结构的一些基本误解,然后我会强调层级一致性的本质和重要性。我们可以用分形标度来检验城市形体——作为城市成功的一个前提;另一个独立标度是连通性,应当从拓扑学角度进行研究。用生物系统进化和因特网的知识来讨论尺度分布、逆幂律度尺度法则和"小世界"网络。这些概念表明当代都市一方面向郊区化蔓延发展,另一方面是摩天楼式发展——这种对极端密度的偏好都是病态的。当代都市面临的挑战是如何用最佳方式实现竞争性连接网络的融合。

Synchronization and Control of Halo-Chaos in Beam Transport Network with Small World Topology

The synchronous conditions of two kinds of the small-world （SW） network are studied. The small world topology can affect on dynamical behaviors of the beam transport network （BTN） largely, if the BTN is constructed with the SW topology, the global linear coupling and special linear feedback can realize the synchronization control of beam halo-chaos as well as periodic state in the BTN with the SW topology, respectively. This important result can provide an effective way for the experimental study and the engineering design of the BTN in the high-current accelerator driven radioactive clean nuclear power systems, and may have potential use in prospective applications for halo-chaos secure communication.

The classification and analysis of dynamic networks

In this paper we, firstly, classify the complex networks in which the nodes are of the lifetime distribution. Secondly, in order to study complex networks in terms of queuing system and homogeneous Markov chain, we establish the relation between the complex networks and queuing system, providing a new way of studying complex networks. Thirdly, we prove that there exist stationary degree distributions of M-G-P network, and obtain the analytic expression of the distribution by means of Markov chain theory. We also obtain the average path length and clustering coefficient of the network. The results show that M-G-P network is not only scale-free but also of a small-world feature in proper conditions.

Nonlinear Dynamical Behavior in Neuron Model Based on Small World Network with Attack and Repair Strategy

In this paper, we investigate the effect due to the change of topology structure of network on the nonlinear dynamical behavior, by virtue of the OFC neuron evolution model with attack and repair strategy based on the small world. In particular, roles of various parameters relating to the dynamical behavior are carefully studied and analyzed. In addition, the avalanche and EEC-like wave activities with attack and repair strategy are also explored in detail in this work.

Study Under AC Stimulation on Excitement Properties of Weighted Small-World Biological Neural Networks with Side-Restrain Mechanism

In this paper, we propose a new model of weighted small-world biological neural networks based on biophysical Hodgkin-Huxley neurons with side-restrain mechanism. Then we study excitement properties of the model under alternating current （AC） stimulation. The study shows that the excitement properties in the networks are preferably consistent with the behavior properties of a brain nervous system under different AC stimuli, such as refractory period and the brain neural excitement response induced by different intensities of noise and coupling. The results of the study have reference worthiness for the brain nerve electrophysiology and epistemological science.

Global optimization by small-world optimization algorithm based on social relationship network

A fast global convergence algorithm, small-world optimization (SWO), was designed to solve the global optimization problems, which was inspired from small-world theory and six degrees of separation principle in sociology. Firstly, the solution space was organized into a small-world network model based on social relationship network. Secondly, a simple search strategy was adopted to navigate into this network in order to realize the optimization. In SWO, the two operators for searching the short-range contacts and long-range contacts in small-world network were corresponding to the exploitation and exploration, which have been revealed as the common features in many intelligent algorithms. The proposed algorithm was validated via popular benchmark functions and engineering problems. And also the impacts of parameters were studied. The simulation results indicate that because of the small-world theory, it is suitable for heuristic methods to search targets efficiently in this constructed small-world network model. It is not easy for each test mail to fall into a local trap by shifting into two mapping spaces in order to accelerate the convergence speed. Compared with some classical algorithms, SWO is inherited with optimal features and outstanding in convergence speed. Thus, the algorithm can be considered as a good alternative to solve global optimization problems.

Complex Behavior in a Selective Aging Neuron Model Based on Small World Networks

Complex behavior in a selective aging simple neuron model based on small world networks is investigated. The basic elements of the model are endowed with the main features of a neuron function. The structure of the selective aging neuron model is discussed. We also give some properties of the new network and find that the neuron model displays a power-law behavior. If the brain network is small world-like network, the mean avalanche size is almost the same unless the aging parameter is big enough.

Dynamic Evolution with Limited Learning Information on a Small-World Network

This paper investigates the dynamic evolution with limited learning information on a small-world network.In the system, the information among the interaction players is not very lucid, and the players are not allowed to inspectthe profit collected by its neighbors, thus the focal player cannot choose randomly a neighbor or the wealthiest one andcompare its payoff to copy its strategy.It is assumed that the information acquainted by the player declines in theform of the exponential with the geographical distance between the players, and a parameter V is introduced to denotethe inspect-ability about the players.It is found that under the hospitable conditions, cooperation increases with therandomness and is inhibited by the large connectivity for the prisoner's dilemma; however, cooperation is maximal atthe moderate rewiring probability and is chaos with the connectivity for the snowdrift game.For the two games, theacuminous sight is in favor of the cooperation under the hospitable conditions; whereas, the myopic eyes are advantageousto cooperation and cooperation increases with the randomness under the hostile condition.

Spiral Wave in Small-World Networks of Hodgkin-Huxley Neurons

The effect of small-world connection and noise on of Hodgkin-Huxley neurons are investigated in detail. Some the formation and transition of spiral wave in the networks interesting results are found in our numerical studies, i） The quiescent neurons are activated to propagate electric signal to others by generating and developing spiral wave from spiral seed in small area. ii） A statistical factor is defined to describe the collective properties and phase transition induced by the topology of networks and noise, iii） Stable rotating spiral wave can be generated and keeps robust when the rewiring probability is below certain threshold, otherwise, spiral wave can not be developed from the spiral seed and spiral wave breakup occurs for a stable rotating spiral wave. iv） Gaussian white noise is introduced on the membrane of neurons to study the noise-induced phase transition on spiral wave in small-world networks of neurons. It is confirmed that Ganssian white noise plays active role in supporting and developing spiral wave in the networks of neurons, and appearance of smaller factor of synchronization indicates high possibility to induce spiral wave.

Effects of Aging and Self-organized Criticality in a Pulse-Coupled Integrate-and-Fire Neuron Model Based on Small World Networks

Effects of aging and self-organized criticality in a pulse-coupled integrate-and-fire neuron model based on small world networks have been studied. We give the degree distribution of aging network, average shortest path length, the diameter of our network, and the clustering coefficient, and find that our neuron model displays the power-law behavior, and with the number of added links increasing, the effects of aging become smaller and smaller. This shows that if the brain works at the self-organized criticality state, it can relieve some effects caused by aging.

Adaptive Synchronization in Small-World Dynamical Networks

Adaptive synchronization in NW small-world dynamical networks was studied. Firstly, an adaptive synchronization method is presented and explained. Then, it is applied to two different classes of dynamical networks, one is a class-B network, small-world connected R6 ssler oscillators, the other is a class-A network, small-world connected Chua＇s circuits. The simulation verifies the validity of the presented method. It also shows that the adaptive synchronization method is robust to the variations of the node systems parameters. So the presented method can be used in networks whose node systems have unknown or time-varying parameters.

Phase Transitions of an Epidemic Spreading Model in Small-World Networks

We propose a modified susceptible-infected-refractory-susceptible （SIRS） model to investigate the global oscillations of the epidemic spreading in Watts-Strogatz （WS） small-world networks. It is found that when an individual immunity does not change or decays slowly in an immune period, the system can exhibit complex transition from an infecting stationary state to a large amplitude sustained oscillation or an absorbing state with no infection. When the immunity decays rapidly in the immune period, the transition to the global oscillation disappears and there is no oscillation. Furthermore, based on the spatico-temporal evolution patterns and the phase diagram, it is disclosed that a long immunity period takes an important role in the emergence of the global oscillation in small-world networks.

Small World Effects in a Harmonious Unifying Hybrid Preferential Model Networks

Small worm effects in the harmonious unifying hybrid preferential model （HUHPM） networks are studied both numerically and analytically. The idea and method of the HUHPM is applied to three typical examples of unweighted BA model, weighted BBV model, and the TDE rnodel, so-called HUHPM-BA, HUHPM-BBV and HUHPM- TDE networks. Comparing the HUHPM with current typical models above, it is found that the HUHPM networks has the smallest average path length and the biggest average clustering coefficient. The results demonstrate that the HUHPM is more suitable not only for the un-iveighted models but also for the weighted models.

基于二分图的城市公交网络拓扑性质研究

以北京市公交系统为例,用二分图模型对其进行描述,分别构建出公交站点网络和公交线路网络,对二分图、公交站点网络和公交线路网络进行了度的分布、集聚系数以及平均路径长度等拓扑参数的计算,并与规则网络和随机网络进行了比较,发现北京市公交系统具有"小世界"网络的性质.最后深入地研究了公交线路网络与公交站点网络拓扑参数形成的机理.

PREVENTING RUMOR SPREADING ON SMALL-WORLD NETWORKS

Since the spreading of harmful rumors can deeply endanger a society, it is valuable to investigate strategies that can efficiently prevent hazardous rumor propagation. To conduct this investigation, the authors modify the SIR model to describe rumor propagation on networks, and apply two major immunization strategies, namely, the random immunization and the targeted immunization to the rumor model on a small-world network. The authors find that when the average degree of the network is small, both two strategies are effective and when the average degree is large, neither strategy is efficient in preventing rumor propagation. In the latter case, the authors propose a new strategy by decreasing the credibility of the rumor and applying either the random or the targeted immunization at the same time. Numerical simulations indicate that this strategy is effective in preventing rumor spreading on the small-world network with large average degree.