基于社会依赖演化网的协同过程调控框架

针对跨管理域服务协同过程所面临的不可控制障碍,该文革新社会依赖表示理论以支持协同状态的变迁和过程演化。提出开发基于社会依赖演化网(SDEN)的协同过程调控框架,由社会依赖规范构成的SDEN、协同过程自管理机制驱动的执行规范的理性Agents和社会承诺、承诺监管、信誉管理机制构成的社区协同监管体系3项技术组成。实验结果证明,该框架技术和方法可以主动检测并应对协同执行过程中出现的节点失效、服务超时、服务中断、支付违约等服务异常情况,使跨管理域协同过程变得可预测、可控和可信。

试论语言演化网络——以藏缅语为例

文章回顾了演化树理论产生、发展的历史,分析了演化树理论对于语言演化研究的不足之处,介绍了生物学中演化网思想和演化网重建方法诞生的理论背景及其在语言演化研究中的应用情况。此外,文章以中国境内的藏缅语族语言为例,以NeighborNet演化网生成方法重建了藏缅语演化网,分析了演化网图对于重新理解藏缅语演化历史的启示。

基于企业污染行为视角的网络舆情危机演化研究——以环境事件为例

网络舆情和环境保护等是诱发企业危机的重要因素之一,但有关企业污染行为诱发网络舆情危机形成机理的研究成果并不多见。以2011年社会普遍关注的环境污染事件为例,通过实证方法和演化理论对企业行为诱导的媒体报道行为进行了分析,然后对企业行为诱发的网众网络舆情传播行为进行了研究,分析了企业行为导致的环境网络舆情危机形成的原因。

基于嵌入黏聚单元法的页岩储层压裂缝网扩展规律

页岩储层压裂后形成的裂缝网络是页岩气有效开发的基础和关键,体积压裂过程中,对天然裂缝的发育形态的认识与人工裂缝的控制是压裂改造的关键和难点问题。为此,以四川盆地南部地区奥陶系五峰组—志留系龙马溪组页岩储层为研究对象,基于批量嵌入黏聚单元法(BCZM)以及牵引—分离损伤理论(Traction—Separation Law,TSL)对天然裂缝空间展布及性质进行表征,并建立了富集天然裂缝网群的页岩储层有限元模型,分析了人工裂缝与水平层理、天然裂缝交汇的裂缝网演化规律。研究结果表明:(1)压裂过程中,压裂液会优先沿水平层理与人工主裂缝方向流动,驱使主裂缝不断与天然裂缝进行沟通,最终形成类似星形包络线的压裂改造区域;(2)星形改造区域关于井眼呈现对称分布,随着压裂作业的进行,当有效改造半径达到一定值后,改造区域几何面积趋于稳定;(3)井口压裂液注入排量对压裂缝网形态影响较大,实际施工时应选择合适的注入排量,过小的压裂排量会使地层中液体压力难以打开天然裂缝,而过大的排量又会导致人工水力主裂缝直接穿越天然裂缝而被层理捕获,最终不能形成复杂有效的网状裂缝。结论认为,开展页岩储层压裂缝网演化模拟对认识、预测及控制页岩储层压裂缝网形态具有重要的理论指导意义,将有助力我国深层页岩气开发。

Simultaneous Identification of Thermophysical Properties of Semitransparent Media Using a Hybrid Model Based on Artificial Neural Network and Evolutionary Algorithm

A hybrid identification model based on multilayer artificial neural networks(ANNs) and particle swarm optimization(PSO) algorithm is developed to improve the simultaneous identification efficiency of thermal conductivity and effective absorption coefficient of semitransparent materials.For the direct model,the spherical harmonic method and the finite volume method are used to solve the coupled conduction-radiation heat transfer problem in an absorbing,emitting,and non-scattering 2D axisymmetric gray medium in the background of laser flash method.For the identification part,firstly,the temperature field and the incident radiation field in different positions are chosen as observables.Then,a traditional identification model based on PSO algorithm is established.Finally,multilayer ANNs are built to fit and replace the direct model in the traditional identification model to speed up the identification process.The results show that compared with the traditional identification model,the time cost of the hybrid identification model is reduced by about 1 000 times.Besides,the hybrid identification model remains a high level of accuracy even with measurement errors.

A Weighted Evolving Network with Community Size Preferential Attachment

Community structure is an important characteristic in real complex network.It is a network consists ofgroups of nodes within which links are dense but among which links are sparse.In this paper, the evolving network includenode, link and community growth and we apply the community size preferential attachment and strength preferentialattachment to a growing weighted network model and utilize weight assigning mechanism from BBV model.Theresulting network reflects the intrinsic community structure with generalized power-law distributions of nodes'degreesand strengths.

Revenue optimization strategy of V2G based on evolutionary game

In order to protect the interests of electric vehicle users and grid companies with vehicle-to-grid(V2G)technology,a reasonable electric vehicle discharge electricity price is established through the evolutionary game model.A game model of power grid companies and electric vehicle users based on the evolutionary game theory is established to balance the revenue of both players in the game.By studying the dynamic evolution process of both sides of the game,the range of discharge price that satisfies the interests of both sides is obtained.The results are compared with those obtained by the static Bayesian game.The results show that the discharge price which can benefit both sides of the game exists in a specific range.According to the setting of the example,the reasonable discharge electricity price is 1.1060 to 1.4811 yuan/(kW·h).Only within this range can the power grid company and electric vehicle users achieve positive interactions.In addition,the evolutionary game model is easier to balance the interests of the two players than the static Bayesian game.

Horror Video Recognition Based on Fuzzy Comprehensive Evolution

Technique for horror video recognition is important for its application in web content filtering and surveillance, especially for preventing children from being threaten. In this paper, a novel horror video recognition algorithm based on fuzzy comprehensive evolution model is proposed. Three low-level video features are extracted as typical features, and they are video key-light, video colour energy and video rhythm. Analytic Hierarchy Process （AHP） is adopted to estimate the weights of extracted features in fuzzy evolution model. Horror evaluation （membership function） is on shot scale and it is constructed based on the knowledge that videos which share the same affective have similar low-level features. K-Means algorithm is implemented to help finding the most representative feature vectors. The experimental results demonstrate that the proposed approach has good performance in recognition precision, recall rate and F1 measure.

Evolution Properties of Modules in Complex Networks

In complex networks, network modules play a center role, which carry out a key function. In this paper, we introduce the spatial correIation function to describe the relationships among the network modules. Our focus is to investigate how the network modules evolve, and what the evolution properties of the modules are. In order to test the proposed method, as the examples, we use our method to analyze and discuss the ER random network and scale-free network. Rigorous analysis of the existing data shows that the introduced correlation function is suitable for describing the evolution properties of network modules. Remarkably, the numerical simulations indicate that the ER random network and scale-free network have different evolution properties.

Research on E-mail Communication Network Evolution Model Based on User Information Propagation

E-mail communication network evolution model based on user information propagation is studied. First, mathematical representation of weighted e-mail communication network is proposed, and network center parameters of Enron dataset and the distribution of node degree and strength are analyzed. Then, some rules of e-mail communication network evolution are found. Second, the model of e-mail information propagation is described, and e-mail communication network evolution model based on user information propagation is proposed. Lastly, the simulation proves the correctness of the distribution characteristic of degree and strength of the model proposed and then verifies that the model proposed is closer to the real situation of e-mail communication network through parameter comparison. This research provides the basis for other researches on social network evolution and data communication.

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.

Maritime Clusters＇ Evolution： A Digital Innovation Model

Maritime cluster is a well-established and productively researched theme by maritime policy and economics scholars. Maritime cluster＇s evolution is an under-investigated area, with ramifications in maritime policy and business decision-making. In this paper, we study the evolutionary formation of maritime clusters, in the contemporary European blue economy context. We examine pertinent factors for the sustainable development of maritime clusters, with a strong technical, service and market innovation orientation. We merely examine the significance of legislative, financial, business networking and knowledge management related components. Qualitative empirical testing of the theoretical premises is performed for the Spanish, Italian, Greek and Cypriot cluster entities.

Research on Public Opinion Transmission and Evolution Mechanism in Network

As the Internet continues to expand, the influence of network information on real life has gradually deepened. Research on propagation and evolution of Internet public opinion has become a hot topic. The force of intemet public opinion penetrates and influences on every aspect of the society. Compared with traditional public opinion, the network public opinion has features of immediate, multivariate and interactive, the propagation behavior has the new change compared with the traditional public opinion. In the propagation behavior of network public opinion, agenda setting is no longer an arbitrary, the influence of opinion leaders in the agenda setting becomes more and more complex and diversified. The formation time of network public opinion is short, and social influence becomes strong. Guide the public opinion to build a harmonious environment of network public opinion. Overall, our country＇ s network public opinion environment is a benign situation and steadily promoting the reforms of public policies. Although there is still a few not rational voices full of them, the network public opinion shows a general trend of positive thinking. Based on this philosophy, through the research of network public opinion dissemination and evolution mechanism, can be all-round good guidance and supervision of public opinion, building a harmonious network environment of public opinion.

An evolutionary game based security decision algorithm for wireless sensor networks

When using traditional game methods to study information security of the wireless sensor networks,players are mostly based on the assumption of completely rational.Based on bounded rationality,the evolutionary game theory is used to establish the attack-defense model,analyze the strategy selection process of players,solve the evolutionarily stable strategy and design the optimal strategy selection algorithm.Then,considering the strategy dependence,the incentive and punishment mechanism is introduced to improve the replicator dynamic equation.The simulation results show that the model is reasonable and the algorithm is effective,which provides new theoretical support for the security of wireless sensor networks.

Research on the Evolution of Thinking Dynamics Attractor

In this paper we introduce the evolution law of thinking-neural network attractor in the field of thinking dynamics,a new idea about the attractor evolution using evolutional mapping transformation is given on the bases of generalized isologous concept. The idea is connected with the intuitive thinking.This paper lays a foundation for the further studying of the brain thinking process.

Sites to Remember： Performing the Landscape in Cultural History

This paper aims to compare and contrast two site-specific performance productions, both designed to grapple with processes of cultural remembrance, whilst also operating as successful tourist attractions. The narratives encompassed by both productions revolve around shared Australian histories, for audiences attracted by place and what it is able to represent. Re-enactments of past events call into the present a consideration of what still remains, with both shows enabling new subjective interpretations of earlier times. The defining difference between the two, however, rests in the context of each performance, in the one case as a commodification of heritage and in the other case as the desire to produce an artistic yet popular theatrical product. Ballarat＇s, Sovereign Hill＇s light and sound show, Blood on the Southern Cross celebrates and commemorates, in mega-spectacle style, the Eureka Stockade, one of Australia＇s key historical events. Using a mechanised display of the original goldmining site of the Eureka rebellion, the performance is operated by computers with video-projection, multi-phonic sound, and moving model forms, with audiences moved around the massive site on transporters. The Piccolo Tales, a contrasting performance most notably in terms of size, unfolds the history of Kings Cross, through its setting in the miniscule iconic Piccolo Bar, in one of the tiny side streets of Sydney＇s bustling and densest suburb. This paper encompasses an investigation of how the cultural inscriptions of the two specific sites interweave with the performance styles, materials, political and social positioning of the works. Previous performance studies examining site-specificity are utilised, including the author＇s analysis of particular festival performances as ＂place-making＂ （Hayes, 2012, 2013）. Smith＇s （2009） model of ＂signposts＂ is used to consider acting within site-specific productions in a new light, whilst both performances are more completely analysed through Schneider＇s （2011） concept of incomplete pasts forming ＂cycles of memory＂.

A KAD Network Evolution Model Based on Node Behavior

An evolution model of KAD Dynamic Model Network(KDMN) is proposed to study the reason of hot node and simulate the process of network evolution based on node behavior from a holistic perspective.First,some symbols and meanings are introduced to describe nodes relationship and network states at a time step.Second,some evolution rules for network are formulated when node behaviors of join,exit,routing table update,data retrieval and content index distribution happen with different contextual scene in KAD network.In addition,a lightweight simulator is designed to implement the KDMN model.Moreover,an example of how to use the simulator to simulate the network changes in order to observe the result is described in detail.Finally,the KDMN is applied to analyze the reason for the formation of hot nodes in the BT and eMule network in the experiment.The different evolution principles of local priority,global priority and hybrid random are adopted based on the provision of network protocol of BT and eMule.The result of this experiment demonstrates that there are some hot nodes exist in the KAD network.However,the principle of hybrid random can effectively alleviate the phenomenon that a node is widely linked with others compared with global and local priority.

Technological Innovation Collaboration Network Evolution Simulation and Empirical Research

The technology innovation cooperation relationship of enterprises has evolved into the representation of complicated network. MATLAB software is used for computer simulation on network evolution process of technology innovation cooperation, and Ucinet characterization analysis software is used to compute characteristic values of simulation network such as power law index of network, average route length and accumulation coefficients. It is compared with the actual network, and the simulation results are analyzed to verify the rationality of the constructed evolution model.

A novel weighted evolving network model based on clique overlapping growth

A novel weighted evolving network model based on the clique overlapping growth was proposed.The model shows different network characteristics under two different selection mechanisms that are preferential selection and random selection.On the basis of mean-field theory,this model under the two different selection mechanisms was analyzed.The analytic equations of distributions of the number of cliques that a vertex joins and the vertex strength of the model were given.It is proved that both distributions follow the scale-free power-law distribution in preferential selection mechanism and the exponential distribution in random selection mechanism,respectively.The analytic expressions of exponents of corresponding distributions were obtained.The agreement between the simulations and analytical results indicates the validity of the theoretical analysis.Finally,three real transport bus networks(BTNs) of Beijing,Shanghai and Hangzhou in China were studied.By analyzing their network properties,it is discovered that these real BTNs belong to a kind of weighted evolving network model with clique overlapping growth and random selection mechanism that was proposed in this context.

Collaboration strategy for software dynamic evolution of multi-agent system

As the ability of a single agent is limited while information and resources in multi-agent systems are distributed, cooperation is necessary for agents to accomplish a complex task. In the open and changeable environment on the Internet, it is of great significance to research a system flexible and capable in dynamic evolution that can find a collaboration method for agents which can be used in dynamic evolution process. With such a method, agents accomplish tasks for an overall target and at the same time, the collaborative relationship of agents can be adjusted with the change of environment. A method of task decomposition and collaboration of agents by improved contract net protocol is introduced. Finally, analysis on the result of the experiments is performed to verify the improved contract net protocol can greatly increase the efficiency of communication and collaboration in multi-agent system.