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Articles de revues sur le sujet "Small world scale-free transportation network"
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Shang, Jun, Hao Qiang Liu, Qiang Liu et Zi Qi Liu. « Design of the Small World Model by NS2 ». Applied Mechanics and Materials 496-500 (janvier 2014) : 2338–41. http://dx.doi.org/10.4028/www.scientific.net/amm.496-500.2338.
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WSN is the network which is used mostly in the world nowadays, and it has the characteristics that lower cost and better functions than other kinds of the network, and the WSN network is built by the ordinary nodes and the super nodes.Theoretical study of the complex network is widely involved in the fields of computer networks, and the applied research becomes more and more important in the future. It has caused many academic attention about how to apply the complex network theory among the specific application in recent years. In the complex network theory, there has been a number of important research results about the use of the small-world network, scale-free network in the field of transportation.
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Tarapata, Zbigniew. « Modelling and analysis of transportation networks using complex networks : Poland case study ». Archives of Transport 36, no 4 (31 décembre 2015) : 55–65. http://dx.doi.org/10.5604/08669546.1185207.
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In the paper a theoretical bases and empirical results deal with analysis and modelling of transportation networks in Poland using complex networks have been presented. Properties of complex networks (Scale Free and Small World) and network's characteristic measures have been described. In this context, results of empirical researches connected with characteristics of passenger air links network, express railway links network (EuroCity and InterCity) and expressways/highways network in Poland have been given. For passenger air links network in Poland results are compared with the same networks in USA, China, India, Italy and Spain. In the conclusion some suggestions, observations and perspective dealing with complex network in transportation networks have been presented.
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Wang, Yong, et Ta Zhou. « Complexity Analysis of Public Transportation Network in Zhangjiagang City Using Complex Network Theory ». Advanced Materials Research 546-547 (juillet 2012) : 1211–16. http://dx.doi.org/10.4028/www.scientific.net/amr.546-547.1211.
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Public transportation network has been proven that it can be simulated as a complex network. In this paper, a bus transport system of Zhangjiagang city is considered. Network degree distribution, average path length, and clustering coefficient are utilized as criteria to analyze as the complexity of the network. Experimental results show that the network which is in line with power-law distribution has a smaller average path length and a large clustering coefficient. It also indicates that, the networks of Zhangjiagang public bus system are not a small-world network with scale-free property.
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Trobajo, M. T., et M. V. Carriegos. « Spanish Airport Network Structure : Topological Characterization ». Computational and Mathematical Methods 2022 (9 avril 2022) : 1–9. http://dx.doi.org/10.1155/2022/4952613.
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Applied complex network theory has become an interesting research field in the last years. Many papers have appeared on this subject dealing with the topological description of real transport systems, from small networks like the Italian airport network to the worldwide air transportation network. A comprehensive topological description of those critical structures is relevant in order to understand their dynamics, capacities, and vulnerabilities. In this work, for the first time, we describe the Spanish airport network (SAN) as a complex network. Nodes are airports, and links are flight connections weighed by traffic flow. We study its topological features and traffic dynamics. Our analysis shows that SAN has complex dynamics similar to small-size air transportation networks of other developed economies. It shares properties of small-world and scale-free networks, and it is highly connected and efficient and has a disassortative pattern for high-degree nodes.
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ZHAO, HUI, et ZIYOU GAO. « GENERALIZED SHORTEST PATH AND TRAFFIC EQUILIBRIUM IN COMPLEX TRANSPORTATION NETWORKS ». Modern Physics Letters B 21, no 20 (30 août 2007) : 1343–49. http://dx.doi.org/10.1142/s021798490701350x.
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Shortest path plays an important role in the study of complex networks. But in real transportation systems, choosing the shortest path may not be the best way for the drivers. Based on the traffic equilibrium theory, we generalize the concept of shortest path. Flux distribution is also investigated by using the generalized concept on various types of complex networks. We find that the flux differs little in all the edges of lattice while in small-world and scale-free networks, the flux distribution follows a power law, and in the random network, the flux distribution has an exponential tail. We consider lattice may be the optimal topology in design a transportation network.
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Chong, Pengyun, Bin Shuai, Shaowei Deng, Jianting Yang et Hui Yin. « Analysis on Topological Properties of Dalian Hazardous Materials Road Transportation Network ». Mathematical Problems in Engineering 2015 (2015) : 1–11. http://dx.doi.org/10.1155/2015/340780.
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To analyze the topological properties of hazardous materials road transportation network (HMRTN), this paper proposed two different ways to construct the cyberspace of HMRTN and constructed their complex network models, respectively. One was the physical network model of HMRTN based on the primal approach and the other was the service network model of HMRTN based on neighboring nodes. The two complex network models were built by using the case of Dalian HMRTN. The physical network model contained 154 nodes and 238 edges, and the statistical analysis results showed that (1) the cumulative node degree of physical network was subjected to exponential distribution, showing the network properties of random network and that (2) the HMRTN had small characteristic path length and large network clustering coefficient, which was a typical small-world network. The service network model contained 569 nodes and 1318 edges, and the statistical analysis results showed that (1) the cumulative node degree of service network was subjected to power-law distribution, showing the network properties of scale-free network and that (2) the relationship between nodes strength and their descending order ordinal and the relationship between nodes strength and cumulative nodes strength were both subjected to power-law distribution, also showing the network properties of scale-free network.
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De Bona, A. A., K. V. O. Fonseca, M. O. Rosa, R. Lüders et M. R. B. S. Delgado. « Analysis of Public Bus Transportation of a Brazilian City Based on the Theory of Complex Networks Using the P-Space ». Mathematical Problems in Engineering 2016 (2016) : 1–12. http://dx.doi.org/10.1155/2016/3898762.
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The city of Curitiba, located at Southern Brazil, is recognized by its urban planning structured on three pillars: land use, collective transportation, and traffic. With 3.8 million people in its metropolitan area, the public transport system deals with approximately 2.5 million passengers daily. The structure and properties of such a transportation system have substantial implications for the urban planning and public politics for sustainable development of Curitiba. Therefore, this paper analyzes the structure of the public transportation system of Curitiba through the theory of complex networks in a static approach of network topology and presents a comparative analysis of the results from Curitiba, three cities from China (Shanghai, Beijing, and Guangzhou), and three cities from Poland (GOP, Warszawa, and Łódź). The transportation network was modeled as a complex network with exact geographical coordinates of its bus stops. In all bus lines, the method used was the P-Space. The results show that this bus network has characteristics of both small-world and scale-free networks.
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Zhang, Ling, Jingjing Hao, Xiaofeng Ji et Lan Liu. « Research on the Complex Characteristics of Freight Transportation from a Multiscale Perspective Using Freight Vehicle Trip Data ». Sustainability 11, no 7 (29 mars 2019) : 1897. http://dx.doi.org/10.3390/su11071897.
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To better guide the sustainable developing of freight transport aligning with environmental objectives it is of strategic importance to capture freight transportation characteristics more realistically. This paper characterizes freight transportation by using a complex network approach from multidimensional perspectives based on freight vehicle trips data. We first build two subnetworks from prefecture-level city-scale and county-level city-scale. Subsequently, network analysis indices based on complex network theory were applied to examine the topological structure and complexity of the freight transportation networks. Furthermore, the community detection method is introduced to reveal the networks’ clustering characteristics. The findings show that the prefecture-level city-scale network and the county-level city-scale network both have obvious small-world network characteristics, but the prefecture-level city-scale network has higher operating efficiency for goods movement. Additionally, the influence of the cross-border effect on the freight transportation network was verified. In terms of the community structure, the freight network shows distinct clustering features only at the county-level city-scale.
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Ren, Cuiping, Bianbian Chen, Fengjie Xie, Xuan Zhao, Jiaqian Zhang et Xueyan Zhou. « Understanding Hazardous Materials Transportation Accidents Based on Higher-Order Network Theory ». International Journal of Environmental Research and Public Health 19, no 20 (16 octobre 2022) : 13337. http://dx.doi.org/10.3390/ijerph192013337.
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In hazardous materials transportation systems, accident causation analysis is important to transportation safety. Complex network theory can be effectively used to understand the causal factors of and their relationships within accidents. In this paper, a higher-order network method is proposed to establish a hazardous materials transportation accident causation network (HMTACN), which considers the sequences and dependences of causal factors. The HMTACN is composed of 125 first- and 118 higher-order nodes that represent causes, and 545 directed edges that denote complex relationships among causes. By analyzing topological properties, the results show that the HMTACN has the characteristics of small-world networks and displays the properties of scale-free networks. Additionally, critical causal factors and key relationships of the HMTACN are discovered. Moreover, unsafe tank or valve states are important causal factors; and leakage, roll-over, collision, and fire are most likely to trigger chain reactions. Important higher-order nodes are discovered, which can represent key relationships in the HMTACN. For example, unsafe distance and improper operation usually lead to collision and roll-over. These results of higher-order nodes cannot be found by the traditional Markov network model. This study provides a practical way to extract and construct an accident causation network from numerous accident investigation reports. It also provides insights into safety management of hazardous materials transportation.
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Cao, Weiwei, Xiangnan Feng, Jianmin Jia et Hong Zhang. « Characterizing the Structure of the Railway Network in China : A Complex Weighted Network Approach ». Journal of Advanced Transportation 2019 (3 février 2019) : 1–10. http://dx.doi.org/10.1155/2019/3928260.
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Understanding the structure of the Chinese railway network (CRN) is crucial for maintaining its efficiency and planning its future development. To advance our knowledge of CRN, we modeled CRN as a complex weighted network and explored the structural characteristics of the network via statistical evaluations and spatial analysis. Our results show CRN as a small-world network whose train flow obeys power-law decaying, demonstrating that CRN is a mature transportation infrastructure with a scale-free structure. CRN also shows significant spatial heterogeneity and hierarchy in its regionally uneven train flow distribution. We then examined the nodal centralities of CRN using four topological measures: degree, strength, betweenness, and closeness. Nodal degree is positively correlated with strength, betweenness, and closeness. Unlike the common feature of a scale-free network, the most connected nodes in CRN are not necessarily the most central due to underlying geographical, political, and socioeconomic factors. We proposed an integrated measure based on the four centrality measures to identify the global role of each node and the multilayer structure of CRN and confirm that stable connections hold between different layers of CRN.
Thèses sur le sujet "Small world scale-free transportation network"
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Lamanna, Fabio. « Time-related analysis of small world and scale-free transportation networks ». Doctoral thesis, Università degli studi di Trieste, 2008. http://hdl.handle.net/10077/2747.
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2006/2007Coupled biological and chemical systems, neural networks, social interacting species, the Internet and the World Wide Web are only a few examples of Small World and Scale-free complex networks, i.e. systems composed by a large number of highly interconnected dynamical units. During the last ten years these kinds of systems have been the subject of many studies related to comprehend their common structural properties and their dynamics. Small World and Scale-free networks are supposed to be very stable and robust structures in case of failures or deliberate attacks on the system. Moreover, due to their well-known properties, they allow to model several real networks in order to find the key elements for a complete and efficient communication activity between nodes. This thesis introduced a new mathematical tool developed by the author called Time=net.work. The latter has got the purpose to extend the above mentioned complex networks theories to transportation systems under a new time-related point of view. Analysis have been taken firstly on Berlin Transportation Network and then to several other test cases. The relative results help in finding statistical properties about the connectivity and the structure of such system both topologically and considering the travel time and the frequency of the scheduled services. This is a new approach on robustness of transportation networks which allows to find which and how many nodes have to assurance their functionality in order to provide a desired Level of Service in case of failures or deliberate attacks.
I sistemi biologici e chimici, le interazioni ed i rapporti sociali, Internet e il World Wide Web sono soltanto alcuni esempi dei cosiddetti sistemi complessi Small World e Scale-free; essi sono particolari strutture di rete composte da un gran numero di unità interconnesse tra loro che scambiano informazioni dinamicamente ed evolvendosi nel tempo. Negli ultimi dieci anni questi particolari sistemi fisici sono stati oggetto di numerosi studi tesi a determinare le proprietà comuni a diversi tipi di rete e le loro dinamiche. Le reti Small World e Scale-free ad esempio, sono state analizzate per la loro stabilità e resistenza in caso di avarie o di attacchi mirati verso particolari elementi del sistema. Grazie alle loro proprietà tali sistemi consentono di modellizzare diversi tipi di reti reali al fine di determinare gli elementi chiave necessari a garantire la più completa efficienza nelle comunicazioni tra i nodi. Questa tesi presenta un nuovo strumento matematico sviluppato dall'autore denominato Time=net.work. Quest'ultimo ha l'obiettivo di estendere le teorie che contraddistinguono i sistemi complessi a reti di trasporto in funzione di caratteristiche temporali. Le analisi hanno riguardato la rete di trasporto pubblico di Berlino ed altri casi di studio. I relativi risultati consentono di ricavare numerose proprietà statistiche riguardo la connettività e le proprietà strutturali di tali sistemi, sia da un punto di vista topologico che da quello legato ai tempi di percorrenza ed alla frequenza dei servizi. Si tratta di un nuovo approccio alla resistenza delle reti di trasporto che permette di ricavare quali e quanti elementi della rete devono garantire il loro completo funzionamento al fine di provvedere un desiderato Livello di Servizio in caso di avarie o di attacchi deliberati al sistema.
XX Ciclo
1977
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Westlund, Johannes, et Jakob Svenningsson. « Examining network properties using breadth-first sampling : A case study of the network spanned by the kth.se domain ». Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-208346.
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Many real life complex networks consists of a tremendous amount of nodes and edges which make them difficult to extract and analyze. This thesis aims to examine what network prop- erties that can be deduced when considering small samples of a complex network and how well they correspond to the characteristics of the complete network. This is of importance as sampling will most likely be the de facto method when analyzing complex networks in the future. The study examine the scale-free property, the small-world property and the com- munity structure of the network spanned by the KTH domain. The method consisted of gathering data about the network through sampling it in a breadth-first manner using a web crawler. The samples was then compared with respect to each property. The results was that good approximations of the scale-free property could be made from small samples of the KTH network. However, no good approximation could be made about the small-world property using the sampling technique. Good approximations about a node’s community affiliation could be observed. However, general conclusions of the com- plete network’s community structures could not be made. To summarize, the result indi- cate that small samples can be used to approximate some properties of the complete KTH network. However, to determine if the result is true for the general case more research is necessary.Komplexa nätverk i vår omvärld består av ett stort antal hörn och kanter vilket gör dem svå- ra att extrahera och analysera. Denna rapport undersöker vilka nätverksegenskaper som kan härledas vid undersökningen av små stickprov av ett nätverk och hur bra dessa representerar egenskaperna hos det fullständiga nätverket. Detta är av betydelse eftersom användandet av små stickprov kommer troligtvis att vara standarden vid undersökningar av nätverk i framtiden. Denna studie undersökte scale-free egenskapen, small-world egenskapen och community strukturen för nätverket som omfattas av KTH domaänen. Metoden innefattade att samla in data om nätverket genom stickprov baserat på en bredden-först sökning. Detta realiserades genom att använda en sökrobot. Sedan jämfördes de olika stickproven med avseende på de olika nätverksegenskaperna. Resultetat visade att nätverkets scale-free egenskap kunde approximaeras med små stickprov. Däremot var det inte möjligt att approximera nätverkets small-world egenskap genom användet av den givna stickprovsmetoden. Goda approximationer observerades för att avgöra ett hörns community tillhörighet men den allmäna community strukturen kunde inte approximeras. Sammanfattningsvis visade resultatet att stickprov kan användas för att approximera vissa egenskaper hos det fullständiga KTH nätverket men att mer forskning krävs för att avgöra om resultaten kan generaliseras.
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Sun, Xiaowei. « Comparative Analysis of Urban Morphology : Evaluating Space Syntax and Traditional Morphological Methods ». Thesis, Högskolan i Gävle, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-15492.
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This thesis examines the urban morphology of fifty cities using spatial syntax analysis. The analysis compares the urban street networks of European, USA, Islamic and East Asian cities. Street connectivity was the main metric and natural roads were the basis for the analysis. The aim of the study was to analyze determine how sensitive space syntax methods are for uncovering the hierarchical patterns of urban street networks and examining their scale-free and small-world properties. Street data was collected from OpenStreetMap. ArcGIS 10 with the Axwoman extension was used to study the hierarchical levels of street networks. Matlab provided the platform to examine the scale-free property of street data. Pajek software was used to measure the small-world behavior. Based on the hierarchical representation, the fifty sample cities were classified into different groups and their scale-free and small-world properties were studied. From a traditionally morphological perspective, it was found that some cities in Europe have a close-knit cellular and organic urban morphology. Cities in the USA exhibit gridiron patterns on the whole. Some Islamic cities have special urban structure with houses grouped around the cul-de-sac lanes. Several of the East Asian cities studied also have grid forms. According to the space syntax analysis, urban street networks that have a connectivity value greater than the average value were less than 40%. The results showed that for most cities, the street connectivity distribution follows a power-law distribution and exhibits scale-free properties. Urban street networks of all sample cities were found to have a small-world property. Space syntax cannot detect all of the morphological patterns recognized in traditional morphological studies. The method can, however, efficiently quantify the spatial configuration of a large sample. Space syntax’s topological and scaling metrics thus provide a way to compare urban street networks. These metrics can thus help classify cities according to their street patterns but also contribute to an understanding of human behavior within and thus the design of urban spaces. For example, an urban street network with a small-world property could have high efficiency for traffic flows at local and global levels and should be considered in further study.
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Abdesselam, Kahina. « Network Distribution and Respondent-Driven Sampling (RDS) Inference About People Who Inject Drugs in Ottawa, Ontario ». Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/38744.
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Respondent-driven sampling (RDS) is very useful in collecting data from individuals in hidden populations, where a sampling frame does not exist. It starts with researchers choosing initial respondents from a group which may be involved in taboo or illegal activities, after which they recruit other peers who belong to the same group. Analysis results in unbiased estimates of population proportions though with strong assumptions about the underlying social network and RDS recruitment process. These assumptions bear little resemblance to reality, and thus compromise the estimation of any means, population proportions or variances inferred from studies. The topology of the contact network, denoted by the number of links each person has, provides insight into the processes of infectious disease spread. The overall objective of the thesis is to identify the topology of an injection drug use network, and critically review the methods developed to produce estimates. The topology of people who inject drugs (PWID) collected by RDS in Ottawa, 2006 was compared with a Poisson distribution, an exponential distribution, a power-law distribution, and a lognormal distribution. The contact distribution was then evaluated against a small-world network characterized by high clustering and low average distances between individuals. Last a systematic review of the methods used to produce RDS mean and variance estimates was conducted. The Poisson distribution, a type of random distribution, was not an appropriate fit for PWID network. However, the PWID network can be classified as a small world network organised with many connections and short distances between people. Prevention of transmission in such networks should be focussed on the most active people (clustered individuals and hubs) as intervention with any others is less effective. The systematic review contained 32 articles which included the development and evaluation of 12 RDS mean and 6 variance estimators. Overall, the majority of estimators perform roughly the
same, with the exception of RDSIEGO which outperformed the 6 other RDS mean estimators. The Tree bootstrap variance estimate does not rely on modelling RDS as a first order Markov (FOM) process, which seems to be the main limitation of the other existing estimators. The lack of FOM as an assumption and the flexible application of this variance estimator to any RDS point estimate make the Tree bootstrapping estimator a more efficient choice.
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Luo, Hongwei, et Hongwei luo@rmit edu au. « Modelling and simulation of large-scale complex networks ». RMIT University. Mathematical and Geospatial Sciences, 2007. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080506.142224.
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Real-world large-scale complex networks such as the Internet, social networks and biological networks have increasingly attracted the interest of researchers from many areas. Accurate modelling of the statistical regularities of these large-scale networks is critical to understand their global evolving structures and local dynamical patterns. Traditionally, the Erdos and Renyi random graph model has helped the investigation of various homogeneous networks. During the past decade, a special computational methodology has emerged to study complex networks, the outcome of which is identified by two models: the Watts and Strogatz small-world model and the Barabasi-Albert scale-free model. At the core of the complex network modelling process is the extraction of characteristics of real-world networks. I have developed computer simulation algorithms for study of the properties of current theoretical models as well as for the measurement of two real-world complex networks, which lead to the isolation of three complex network modelling essentials. The main contribution of the thesis is the introduction and study of a new General Two-Stage growth model (GTS Model), which aims to describe and analyze many common-featured real-world complex networks. The tools we use to create the model and later perform many measurements on it consist of computer simulations, numerical analysis and mathematical derivations. In particular, two major cases of this GTS model have been studied. One is named the U-P model, which employs a new functional form of the network growth rule: a linear combination of preferential attachment and uniform attachment. The degree distribution of the model is first studied by computer simulation, while the exact solution is also obtained analytically. Two other important properties of complex networks: the characteristic path length and the clustering coefficient are also extensively investigated, obtaining either analytically derived solutions or numerical results by computer simulations. Furthermore, I demonstrate that the hub-hub interaction behaves in effect as the link between a network's topology and resilience property. The other is called the Hybrid model, which incorporates two stages of growth and studies the transition behaviour between the Erdos and Renyi random graph model and the Barabasi-Albert scale-free model. The Hybrid model is measured by extensive numerical simulations focusing on its degree distribution, characteristic path length and clustering coefficient. Although either of the two cases serves as a new approach to modelling real-world large-scale complex networks, perhaps more importantly, the general two-stage model provides a new theoretical framework for complex network modelling, which can be extended in many ways besides the two studied in this thesis.
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Zhuang, Yuwen. « Metric Based Automatic Event Segmentation and Network Properties Of Experience Graphs ». The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1337372416.
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Jiang, Jian. « Modeling of complex network, application to road and cultural networks ». Phd thesis, Université du Maine, 2011. http://tel.archives-ouvertes.fr/tel-00691129.
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Many complex systems arising from nature and human society can be described as complex networks. In this dissertation, on the basis of complex network theory, we pay attention to the topological structure of complex network and the dynamics on it. We established models to investigate the influences of the structure on the dynamics of networks and to shed light on some peculiar properties of complex systems. This dissertation includes four parts. In the first part, the empirical properties (degree distribution, clustering coefficient, diameter, and characteristic path length) of urban road network of Le Mans city in France are studied. The degree distribution shows a double power-law which we studied in detail. In the second part, we propose two models to investigate the possible mechanisms leading to the deviation from simple power law. In the first model, probabilistic addition of nodes and links, and rewiring of links are considered; in the second one, only random and preferential link growth is included. The simulation results of the modelling are compared with the real data. In the third part,the probabilistic uncertainty behavior of double power law distribution is investigated. The network optimization and optimal design of scale free network to random failures are discussed from the viewpoint of entropy maximization. We defined equilibrium network ensemble as stationary ensembles of graphs by using some thermodynamics like notions such as "energy", "temperature", "free energy" for network. In the forth part, an union-division model is established to investigate the time evolution of certain networks like cultural or economical networks. In this model, the nodes represent, for example, the cultures. Several quantities such as richness, age, identity, ingredient etc. are used to parameterize the probabilistic evolution of the network. The model offers a long term view on the apparently periodic dynamics of an ensemble of cultural or economic entities in interaction.
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Duarte, Gerdivane Ferreira. « F?sica estat?stica aplicada a sistemas sociais atrav?s do estudo de redes complexas ». Universidade Federal do Rio Grande do Norte, 2014. http://repositorio.ufrn.br:8080/jspui/handle/123456789/18609.
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In this work a study of social networks based on analysis of family names is presented. A basic approach to the mathematical formalism of graphs is developed and then main theoretical models for complex networks are presented aiming to support the analysis of surnames networks models. These, in turn, are worked so as to be drawn leading quantities, such as aggregation coefficient, minimum average path length and connectivity distribution. Based on these quantities, it can be stated that surnames networks are an example of complex network, showing important features such as preferential attachment and small-world character
Neste trabalho ? apresentado um estudo das redes sociais baseado na an?lise dos nomes de fam?lias. Faz-se uma abordagem b?sica do formalismo matem?tico dos grafos e em seguida apresenta-se os principais modelos te?ricos para as Redes Complexas com o objetivo de fundamentar a an?lise das redes dos sobrenomes. Estas, por sua vez, s?o trabalhadas de modo a serem extra?das as principais grandezas, tais como coe ciente de agrega??o, menor caminho m?dio e distribui??o de conectividades. Com base nestas grandezas, pode-se a rmar que as redes de sobrenomes s?o um exemplo de rede complexa, exibindo caracter?sticas importantes como liga??o preferencial e o car?ter de mundo pequeno.
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Hsiao, Ping-Nan, et 蕭炳南. « A Small World with Scale Free Model for Network Communication ». Thesis, 2003. http://ndltd.ncl.edu.tw/handle/67517557425671723948.
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碩士淡江大學
資訊工程學系
91
The small world network model has been popular to describe human social relations and network formed by biological entities such as neurons. The network model achieves small diameter with relatively few links as measured by the ratio of clustering coefficient and the number of links. It is quite natural to consider email communication as similar to social network pattern. Quite surprisingly we find from our empirical study that email network follows a different type of network model that falls into the category of scale-free network. We propose a new network model to describe such communication topology from linked edge, degree and messages size aspect.
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Piersa, Jarosław. « Scale-freeness and small-world phenomenon in information-flow graphs of geometrical neural networks ». Doctoral thesis, 2013. http://depotuw.ceon.pl/handle/item/215.
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In this dissertation we set out to study a simplified model of activation flow in artificial neural networks with geometrical embedding.
The model provides a mathematical description of abstract neural activation transfer in terms, which bear resemblances to multi-value Boltzmann-like evolution.
The activation-preserving constraint mimics a critical regime of the dynamics and, along with accounting for geometrical location of the neurons, makes the system more feasible for modelling of real-world networks.
We focus on scale invariance or scale-freeness and small-world phenomena in the said networks.
Our results clearly confirm presence of both features at the functional level of the activity-flow graph.
We show that the degree distribution preserves a power-law shape with the exponent value approximately equal to -2.
In addition, we present our results concerning characteristic path length in the said graphs, which grows roughly logarithmically with the size of the network, while the clustering coefficient turns out to be relatively high.
Taken together, the clustering and path length ratios are surprisingly high, and thus confirm large both local and global efficiency of the network.
Finally, we compare the properties of activation-flow model to those reported in neurobiological analyses of brain networks recorded with functional magnetic resonance imagining (fMRI).
There is a strong agreement between the shape and exponent value of degree distribution also the clustering and characteristic path lengths are comparable in both the model and medical data.Celem niniejszej rozprawy jest analiza uproszczonego modelu przepływu aktywności w sztucznych sieciach neuronowych zanurzonych w przestrzeni geometrycznej. Przedstawiony model dostarcza matematycznego opisu transferu aktywności w terminach zbliżonych do wielowartościowych maszyn Boltzmanna. Wymóg zachowania stałej sumarycznej aktywności odzwierciedla krytyczność dynamiki i wraz z uwzględnieniem wpływu lokalizacji geometrycznej neuronów sprawia, że system jest bardziej adekwatny do modelowania rzeczywistych sieci. Badania koncentrują się na bezskalowości oraz fenomenie małego świata w wyżej wymienionych sieciach. Uzyskane rezultaty potwierdzają obecność obu własności w omawianych grafach. Pokażemy, że rozkład stopni wejściowych wierzchołków zachowuje się jak funkcja potęgowa z wykładnikiem równym -2. Ponadto prezentujemy wyniki dotyczące charakterystycznej długości ścieżki, który rośnie logarytmicznie wraz z wielkością systemu, podczas gdy współczynnik klasteryzacji okazuje się dość duży. W konsekwencji stosunek klasteryzacji do długości ścieżek jest zaskakująco wysoki, co jest dystynktywną własnością sieci małego świata. Wreszcie, dokonujemy porównania cech omawianego modelu przepływu aktywności z neuro-biologicznymi rezultatami, przedstawionymi w badaniach grafów mózgowych z danych uzyskanych z funkcjonalnego obrazowania z wykorzystaniem rezonansu magnetycznego (fMRI). Wskazujemy silną odpowiedniość pomiędzy kształtem i wartością wykładnika rozkładu stopni, zaś klasteryzacja i charakterystyczna długość ścieżki są porównywalne w modelu i danych medycznych.
Livres sur le sujet "Small world scale-free transportation network"
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Vernizzi, Graziano, et Henri Orland. Complex networks. Sous la direction de Gernot Akemann, Jinho Baik et Philippe Di Francesco. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198744191.013.43.
Texte intégralRésumé :
This article deals with complex networks, and in particular small world and scale free networks. Various networks exhibit the small world phenomenon, including social networks and gene expression networks. The local ordering property of small world networks is typically associated with regular networks such as a 2D square lattice. The small world phenomenon can be observed in most scale free networks, but few small world networks are scale free. The article first provides a brief background on small world networks and two models of scale free graphs before describing the replica method and how it can be applied to calculate the spectral densities of the adjacency matrix and Laplacian matrix of a scale free network. It then shows how the effective medium approximation can be used to treat networks with finite mean degree and concludes with a discussion of the local properties of random matrices associated with complex networks.
Chapitres de livres sur le sujet "Small world scale-free transportation network"
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« Small World and Scale-Free Network Topologies in an Artificial Regulatory Network Model ». Dans Artificial Life IX. The MIT Press, 2004. http://dx.doi.org/10.7551/mitpress/1429.003.0068.
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Stein, Michael D., et Sandro Galea. « Creating Health Is Like Winning at Soccer ». Dans Pained, 3–4. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780197510384.003.0001.
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This chapter presents soccer as a metaphor for how societies can generate health. Health is shaped by the water one drinks; by the air one breathes; by whether one lives in a safe environment where exercise opportunities and healthy food are available; and by social policies that create a world free from inequity. One can imagine these conditions as the 10 soccer players moving the ball upfield, to maximize one’s chance of winning, of staying healthy. The goalie is medicine. It is one’s last resort—what can restore one to health if one gets sick. The chapter then emphasizes the need for a shift in the way people think about health. As in soccer, ten elevenths of one’s effort should be preventive, with medicine being the last line of defense. Health is about medicine, but it is far more about the politics that create the world one lives in; about housing, transportation, and livable wage; about community networks. Indeed, medicine is only a small part of a larger “team” of forces that shape health.
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Nolte, David D. « Network Dynamics ». Dans Introduction to Modern Dynamics, 207–42. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198844624.003.0007.
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A language of nodes and links, degree and moments, and adjacency matrix and distance matrix, among others, is defined and used to capture the wide range of different types and properties of network topologies. Regular graphs and random graphs have fundamentally different connectivities that play a role in dynamic processes such as diffusion and synchronization on a network. Three common random graphs are the Erdös–Rényi (ER) graph, the small-world (SW) graph, and the scale-free (SF) graph. Random graphs give rise to critical phenomena based on static connectivity properties, such as the percolation threshold, but also exhibit dynamical thresholds for the diffusion of states across networks and the synchronization of oscillators. The vaccination threshold for diseases propagating on networks and the global synchronization transition in the Kuramoto model are examples of dynamical processes that can be used to probe network topologies.
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Youssef, Bassant, Scott F. Midkiff et Mohamed R. M. Rizk. « SNAM ». Dans Advanced Methods for Complex Network Analysis, 215–36. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9964-9.ch009.
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Complex networks are characterized by having a scale-free power-law (PL) degree distribution, a small world phenomenon, a high average clustering coefficient, and the emergence of community structure. Most proposed models did not incorporate all of these statistical properties and neglected incorporating the heterogeneous nature of network nodes. Even proposed heterogeneous complex network models were not generalized for different complex networks. We define a novel aspect of node-heterogeneity which is the node connection standard heterogeneity. We introduce our novel model “settling node adaptive model” SNAM which reflects this new nodes' heterogeneous aspect. SNAM was successful in preserving PL degree distribution, small world phenomenon and high clustering coefficient of complex networks. A modified version of SNAM shows the emergence of community structure. We prove using mathematical analysis that networks generated using SNAM have a PL degree distribution.
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« Accelerated Network Traversal Using Multi/Many-Cores ». Dans Advances in Computer and Electrical Engineering, 59–86. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3799-1.ch003.
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New BSP platforms like TOTEM are following a similar approach to Big Data industry-proven frameworks but applied to exploit the potential of HPC heterogeneous nodes that combine multi-cores and GPUs. The performance of platforms under this new paradigm depends on minimizing the computation time of partitions by increasing the suitability of partitions to processors. However, there is a lack of studies on the suitability of parallel architectures for processing different families of graphs, including small-world and scale-free networks. In this chapter, the authors show how to characterize the performance of multi/many-cores when traversing synthetic networks of varying topology in order to reveal the suitability of multi-cores and GPUs for processing different families of graphs.
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Qiu, Yuhu, Tianyang Lyu, Xizhe Zhang et Ruozhou Wang. « Studies on the Decrease Mechanisms of Typical Complex Networks ». Dans Frontiers in Artificial Intelligence and Applications. IOS Press, 2021. http://dx.doi.org/10.3233/faia210293.
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Network decrease caused by the removal of nodes is an important evolution process that is paralleled with network growth. However, many complex network models usually lacked a sound decrease mechanism. Thus, they failed to capture how to cope with decreases in real life. The paper proposed decrease mechanisms for three typical types of networks, including the ER networks, the WS small-world networks and the BA scale-free networks. The proposed mechanisms maintained their key features in continuous and independent decrease processes, such as the random connections of ER networks, the long-range connections based on nearest-coupled network of WS networks and the tendency connections and the scale-free feature of BA networks. Experimental results showed that these mechanisms also maintained other topology characteristics including the degree distribution, clustering coefficient, average length of shortest-paths and diameter during decreases. Our studies also showed that it was quite difficult to find an efficient decrease mechanism for BA networks to withstand the continuous attacks at the high-degree nodes, because of the unequal status of nodes.
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Bansal, Ankush, et Pulkit Anupam Srivastava. « Transcriptomics to Metabolomics ». Dans Advances in Bioinformatics and Biomedical Engineering, 188–206. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2607-0.ch008.
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A lot of omics data is generated in a recent decade which flooded the internet with transcriptomic, genomics, proteomics and metabolomics data. A number of software, tools, and web-servers have developed to analyze the big data omics. This review integrates the various methods that have been employed over the years to interpret the gene regulatory and metabolic networks. It illustrates random networks, scale-free networks, small world network, bipartite networks and other topological analysis which fits in biological networks. Transcriptome to metabolome network is of interest because of key enzymes identification and regulatory hub genes prediction. It also provides an insight into the understanding of omics technologies, generation of data and impact of in-silico analysis on the scientific community.
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Bansal, Ankush, et Pulkit Anupam Srivastava. « Transcriptomics to Metabolomics ». Dans Biotechnology, 361–79. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8903-7.ch014.
Texte intégralRésumé :
A lot of omics data is generated in a recent decade which flooded the internet with transcriptomic, genomics, proteomics and metabolomics data. A number of software, tools, and web-servers have developed to analyze the big data omics. This review integrates the various methods that have been employed over the years to interpret the gene regulatory and metabolic networks. It illustrates random networks, scale-free networks, small world network, bipartite networks and other topological analysis which fits in biological networks. Transcriptome to metabolome network is of interest because of key enzymes identification and regulatory hub genes prediction. It also provides an insight into the understanding of omics technologies, generation of data and impact of in-silico analysis on the scientific community.
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Vrana, Vasiliki G., Dimitrios A. Kydros, Evangelos C. Kehris, Anastasios-Ioannis T. Theocharidis et George I. Kavavasilis. « Top Museums on Instagram ». Dans Research Anthology on Strategies for Using Social Media as a Service and Tool in Business, 1029–55. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-9020-1.ch052.
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Pictures speak louder than words. In this fast-moving world where people hardly have time to read anything, photo-sharing sites become more and more popular. Instagram is being used by millions of people and has created a “sharing ecosystem” that also encourages curation, expression, and produces feedback. Museums are moving quickly to integrate Instagram into their marketing strategies, provide information, engage with audience and connect to other museums Instagram accounts. Taking into consideration that people may not see museum accounts in the same way that the other museum accounts do, the article first describes accounts' performance of the top, most visited museums worldwide and next investigates their interconnection. The analysis uses techniques from social network analysis, including visualization algorithms and calculations of well-established metrics. The research reveals the most important modes of the network by calculating the appropriate centrality metrics and shows that the network formed by the museum Instagram accounts is a scale–free small world network.
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Patterson, Megan S., Michael K. Lemke et Jordan Nelon. « Complex Systems in a Nutshell ». Dans Complex Systems and Population Health, 19–32. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190880743.003.0002.
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This chapter provides an overview of the key foundational concepts and principles of the study of complex systems. First, a definition for system is provided, and the distinctions between complicated and complex systems are demarcated, as are detail, disorganized, organized, and dynamic types of complexity. Common properties across complex systems are defined and described, including stable states and steady states, path dependence, resilience, critical transitions and tipping points, early warning signals, feedback loops, and nonlinearity. This chapter also delves into how complex issues often consist of networks, with random, scale-free, and small world networks defined and network concepts such as degrees, path length, and heterogeneity defined. The concept of emergence is also emphasized, as well as related principles such as adaptation and self-organization. Cardiometabolic disease (and associated comorbidities) is used in this chapter as a thematic population health example.
Actes de conférences sur le sujet "Small world scale-free transportation network"
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Nabati, Rouhollah, Ali Ghaffari Nejad et Ali Yousefi. « EDSS : An extended deterministic scale-free small world network ». Dans 2016 Eighth International Conference on Information and Knowledge Technology (IKT). IEEE, 2016. http://dx.doi.org/10.1109/ikt.2016.7777790.
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Sun, Yuan-yuan, Kai-ning Hou et Xing-yuan Wang. « A Scale-Free Small-World Network from Durer Pentagons ». Dans 2011 Fourth International Workshop on Chaos-Fractals Theories and Applications (IWCFTA). IEEE, 2011. http://dx.doi.org/10.1109/iwcfta.2011.14.
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Chen, Guangping, Jiabo Hao, Zhiyuan Zhang et Yu Tang. « Getting scale-free network from a small world network without growth ». Dans 2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI). IEEE, 2012. http://dx.doi.org/10.1109/icaci.2012.6463112.
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Ma, Fei, Jing Su et Bing Yao. « One small-world scale-free network model having tuned parameters ». Dans 2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). IEEE, 2017. http://dx.doi.org/10.1109/iaeac.2017.8053985.
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Sihua, Yang, Yao Bing, Yao Ming, Chen Xiang-En, Zhang Xiaomin, Wang Hongyu et Yang Chao. « Labelling Sun-Like Graphs from Scale-Free Small-World Network Models ». Dans 2014 Sixth International Conference on Measuring Technology and Mechatronics Automation (ICMTMA). IEEE, 2014. http://dx.doi.org/10.1109/icmtma.2014.93.
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Liu, Dongzhao, Lei Guo, Youxi Wu et Guizhi Xu. « Robustness of the Scale-free Spiking Neural Network with Small-world Property ». Dans 2020 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2020. http://dx.doi.org/10.1109/ssci47803.2020.9308435.
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BERKOWITZ, KATHERINE, RISHABH D. GUHA, OLUWATIMILEHIN OLUWAJIRE et LANDON GRACE. « A MACHINE LEARNING APPROACH FOR IMPACT DAMAGE QUANTIFICATION IN POLYMER MATRIX COMPOSITES ». Dans Proceedings for the American Society for Composites-Thirty Seventh Technical Conference. Destech Publications, Inc., 2022. http://dx.doi.org/10.12783/asc37/36412.
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Largely due to superior properties compared to traditional materials, the use of polymer matrix composites (PMC) has been expanding in several industries such as aerospace, transportation, defense, and marine. However, the anisotropy and nonhomogeneity of these structures contribute to the difficulty in evaluating structural integrity; damage sites can occur at multiple locations and length scales and are hard to track over time. This can lead to unpredictable and expensive failure of a safety-critical structure, thus creating a need for non-destructive evaluation (NDE) techniques which can detect and quantify small-scale damage sites and track their progression. Our research group has improved upon classical microwave techniques to address these needs; utilizing a custom device to move a sample within a resonant cavity and create a spatial map of relative permittivity. We capitalize on the inevitable presence of moisture within the polymer network to detect damage. The differing migration inclinations of absorbed water molecules in a pristine versus a damaged composite alters the respective concentrations of the two chemical states of moisture. The greater concentration of free water molecules residing in the damage sites exhibit highly different relative permittivity when compared to the higher ratio of polymer-bound water molecules in the undamaged areas. Currently, the technique has shown the ability to detect impact damage across a range of damage levels and gravimetric moisture contents but is not able to specifically quantify damage extent with regards to impact energy level. The applicability of machine learning (ML) to composite materials is substantial, with uses in areas like manufacturing and design, prediction of structural properties, and damage detection. Using traditional NDE techniques in conjunction with supervised or unsupervised ML has been shown to improve the accuracy, reliability, or efficiency of the existing methods. In this work, we explore the use of a combined unsupervised/supervised ML approach to determine a damage boundary and quantification of single-impact specimens. Dry composite specimens were damaged via drop tower to induce one central impact site of 0, 2, or 3 Joules. After moisture exposure, Entrepreneur Dr, Raleigh, North Carolina 27695, U.S.A. 553 each specimen underwent dielectric mapping, and spatial permittivity maps were created at a variety of gravimetric moisture contents. An unsupervised K-means clustering algorithm was applied to the dielectric data to segment the levels of damage and define a damage boundary. Subsequently, supervised learning was used to quantify damage using features including but not limited to thickness, moisture content, permittivity values of each cluster, and average distance between points in each cluster. A regression model was trained on several samples with impact energy as the predicted variable. Evaluation was then performed based on prediction accuracy for samples in which the impact energies are not known to the model.