30 resultados para Teoria de redes complexas

em Universidade Federal do Rio Grande do Norte(UFRN)


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In this work we study a connection between a non-Gaussian statistics, the Kaniadakis statistics, and Complex Networks. We show that the degree distribution P(k)of a scale free-network, can be calculated using a maximization of information entropy in the context of non-gaussian statistics. As an example, a numerical analysis based on the preferential attachment growth model is discussed, as well as a numerical behavior of the Kaniadakis and Tsallis degree distribution is compared. We also analyze the diffusive epidemic process (DEP) on a regular lattice one-dimensional. The model is composed of A (healthy) and B (sick) species that independently diffusive on lattice with diffusion rates DA and DB for which the probabilistic dynamical rule A + B → 2B and B → A. This model belongs to the category of non-equilibrium systems with an absorbing state and a phase transition between active an inactive states. We investigate the critical behavior of the DEP using an auto-adaptive algorithm to find critical points: the method of automatic searching for critical points (MASCP). We compare our results with the literature and we find that the MASCP successfully finds the critical exponents 1/ѵ and 1/zѵ in all the cases DA =DB, DA DB. The simulations show that the DEP has the same critical exponents as are expected from field-theoretical arguments. Moreover, we find that, contrary to a renormalization group prediction, the system does not show a discontinuous phase transition in the regime o DA >DB.

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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

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Este trabalho apresenta um levantamento dos problemas associados à influência da observabilidade e da visualização radial no projeto de sistemas de monitoramento para redes de grande magnitude e complexidade. Além disso, se propõe a apresentar soluções para parte desses problemas. Através da utilização da Teoria de Redes Complexas, são abordadas duas questões: (i) a localização e a quantidade de nós necessários para garantir uma aquisição de dados capaz de representar o estado da rede de forma efetiva e (ii) a elaboração de um modelo de visualização das informações da rede capaz de ampliar a capacidade de inferência e de entendimento de suas propriedades. A tese estabelece limites teóricos a estas questões e apresenta um estudo sobre a complexidade do monitoramento eficaz, eficiente e escalável de redes

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In this thesis, we address two issues of broad conceptual and practical relevance in the study of complex networks. The first is associated with the topological characterization of networks while the second relates to dynamical processes that occur on top of them. Regarding the first line of study, we initially designed a model for networks growth where preferential attachment includes: (i) connectivity and (ii) homophily (links between sites with similar characteristics are more likely). From this, we observe that the competition between these two aspects leads to a heterogeneous pattern of connections with the topological properties of the network showing quite interesting results. In particular, we emphasize that there is a region where the characteristics of sites play an important role not only for the rate at which they get links, but also for the number of connections which occur between sites with similar and dissimilar characteristics. Finally, we investigate the spread of epidemics on the network topology developed, whereas its dissemination follows the rules of the contact process. Using Monte Carlo simulations, we show that the competition between states (infected/healthy) sites, induces a transition between an active phase (presence of sick) and an inactive (no sick). In this context, we estimate the critical point of the transition phase through the cumulant Binder and ratio between moments of the order parameter. Then, using finite size scaling analysis, we determine the critical exponents associated with this transition

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In this work we analyse the implications of using a power law distribution of vertice's quality in the growth dynamics of a network studied by Bianconi anel Barabási. In particular, we start studying the random networks which characterize or are related to some real situations, for instance the tide movement. In this context of complex networks, we investigate several real networks, as well as we define some important concepts in the network studies. Furthermore, we present the first scale-free network model, which was proposed by Barabási et al., and a modified model studied by Bianconi and Barabási, where now the preferential attachment incorporates the different ability (fitness) of the nodes to compete for links. At the end, our results, discussions and conclusions are presented

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In this work we elaborate and discuss a Complex Network model which presents connectivity scale free probability distribution (power-law degree distribution). In order to do that, we modify the rule of the preferential attachment of the Bianconi-Barabasi model, including a factor which represents the similarity of the sites. The term that corresponds to this similarity is called the affinity, and is obtained by the modulus of the difference between the fitness (or quality) of the sites. This variation in the preferential attachment generates very interesting results, by instance the time evolution of the connectivity, which follows a power-law distribution ki / ( t t0 )fi, where fi indicates the rate to the site gain connections. Certainly this depends on the affinity with other sites. Besides, we will show by numerical simulations results for the average path length and for the clustering coefficient

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Neste trabalho, elaboramos e discutimos uma rede complexa sem escala, ou seja, uma rede cuja distribuição de conectividade segue uma lei de distribuição de potência. Nosso trabalho pode ser resumido da seguinte forma: Para efeito de didática vamos começar com redes aleatórias que estão relacionados com situações reais e artificiais, e depois comentar as redes livres de escala, como proposto por Barabási-Albert (BA). Depois disso, discutimos uma extensão deste modelo, onde Barabasi e Bianconi (BB) incluem a qualidade. Discutimos também o modelo de afinidade, ou seja, (Ver Almeida et al). Finalmente vamos mostrar o nosso modelo, uma extensão do modelo de afinidade dada por e apresentar os resultados correspondentes. Para realizar tal tarefa modificamos a regra de ligação preferencial do modelo de BB colocando um fator que apresenta o grau de probabilidade entre os sítios da rede. Esta quantidade é feita pela diferença entre a qualidade do novo sítio e a qualidade dos anteriores. Este novo parâmetro produz novos resultados interessantes: a distribuição que segue uma lei de especial de potência, expoente apropriado. A evolução temporal da conectividade do sítio também é calculada . Além disso, mostramos também, os resultados que foram obtidos, via simulação numérica, para o menor caminho médio e o coeficiente de agregação da rede gerada pelo nosso modelo, isto é, pelo modelo de afinidade.

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Currently the interest in large-scale systems with a high degree of complexity has been much discussed in the scientific community in various areas of knowledge. As an example, the Internet, protein interaction, collaboration of film actors, among others. To better understand the behavior of interconnected systems, several models in the area of complex networks have been proposed. Barabási and Albert proposed a model in which the connection between the constituents of the system could dynamically and which favors older sites, reproducing a characteristic behavior in some real systems: connectivity distribution of scale invariant. However, this model neglects two factors, among others, observed in real systems: homophily and metrics. Given the importance of these two terms in the global behavior of networks, we propose in this dissertation study a dynamic model of preferential binding to three essential factors that are responsible for competition for links: (i) connectivity (the more connected sites are privileged in the choice of links) (ii) homophily (similar connections between sites are more attractive), (iii) metric (the link is favored by the proximity of the sites). Within this proposal, we analyze the behavior of the distribution of connectivity and dynamic evolution of the network are affected by the metric by A parameter that controls the importance of distance in the preferential binding) and homophily by (characteristic intrinsic site). We realized that the increased importance as the distance in the preferred connection, the connections between sites and become local connectivity distribution is characterized by a typical range. In parallel, we adjust the curves of connectivity distribution, for different values of A, the equation P(k) = P0e

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We present a nestedness index that measures the nestedness pattern of bipartite networks, a problem that arises in theoretical ecology. Our measure is derived using the sum of distances of the occupied elements in the adjacency matrix of the network. This index quantifies directly the deviation of a given matrix from the nested pattern. In the most simple case the distance of the matrix element ai,j is di,j = i+j, the Manhattan distance. A generic distance is obtained as di,j = (i¬ + j¬)1/¬. The nestedness índex is defined by = 1 − where is the temperature of the matrix. We construct the temperature index using two benchmarks: the distance of the complete nested matrix that corresponds to zero temperature and the distance of the average random matrix that is defined as temperature one. We discuss an important feature of the problem: matrix occupancy. We address this question using a metric index ¬ that adjusts for matrix occupancy

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In this thesis we investigate physical problems which present a high degree of complexity using tools and models of Statistical Mechanics. We give a special attention to systems with long-range interactions, such as one-dimensional long-range bondpercolation, complex networks without metric and vehicular traffic. The flux in linear chain (percolation) with bond between first neighbor only happens if pc = 1, but when we consider long-range interactions , the situation is completely different, i.e., the transitions between the percolating phase and non-percolating phase happens for pc < 1. This kind of transition happens even when the system is diluted ( dilution of sites ). Some of these effects are investigated in this work, for example, the extensivity of the system, the relation between critical properties and the dilution, etc. In particular we show that the dilution does not change the universality of the system. In another work, we analyze the implications of using a power law quality distribution for vertices in the growth dynamics of a network studied by Bianconi and Barabási. It incorporates in the preferential attachment the different ability (fitness) of the nodes to compete for links. Finally, we study the vehicular traffic on road networks when it is submitted to an increasing flux of cars. In this way, we develop two models which enable the analysis of the total flux on each road as well as the flux leaving the system and the behavior of the total number of congested roads

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In this thesis we deal with a class of composed networks that are formed by two tree networks, TP and TA, whose end points touches each other through a bipartite network BPA. We explore this network using a functional approach. We are interested in what extend the topology, or the structure, of TX (X = A or P) determines the links of BPA. This composed structure is an useful model in evolutionary biology, where TP and TA are the phylogenetic trees of plants and animals that interact in an ecological community. We use in this thesis two cases of mutualist interactions: frugivory and pollinator networks. We analyse how the phylogeny of TX determines or is correlated with BPA using a Monte Carlo approach. We use the phylogenetic distance among elements that interact with a given species to construct an index κ that quantifies the influence of TX over BPA. The algorithm is based in the assumption that interaction matrices that follows a phylogeny of TX have a total phylogenetic distance smaller than the average distance of an ensemble of Monte Carlo realizations generated by an adequate shuffling data. We find that the phylogeny of animals species has an effect on the ecological matrix that is more marked than plant phylogeny

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This work is a study in the Local Productive Arrangement of confections from Agreste of Pernambuco, as a relevant sector in economic and social aspect. This research has as central aim to understand how the inter-organizational relations influence the collective efficiency of arrangement. The theoretical framework employed highlights the approaches that deal with the benefits of business agglomeration for the develop­ment of firms and regions. It has discussed the approach of small and medium enter­ prises and industrial districts (SCHMITZ, 1997), which introduce the concept of col­ lective efficiency, explaining that only those externalities explained by Marshall (1996) are not sufficient to explain the competitive advantage of enterprises, expand­ing the idea that organizations achieve competitive advantage not acting alone. To examine the influences of relations in the collective efficiency, it has been taken as analytical perspective theory of social networks (GRANOVETTER, 1973, 1985; BURT, 1992; UZZI, 1997) because it has believe that this approach provides subsi­ dies for a structural analysis of social relationships in face the behavior of human ac­tion. By examining the organizations in a social network, you should understand the reason of this establishment of the relationship, their benefits, and as the information flow takes place and density of links between the actors (Powell; SMITH-DOERR, 1994). As for the methods, this study is characterized as a case study, in according to the purposed objectives, in addition to qualitative method. Also, due to recovering of the historical milestones of the arrangement, it is used a sectional approach with longitudinal perspective (VIEIRA, 2004). The primary and secondary data were used in order to understand the evolutionary process of the sector and their inter-actors re­ lationships in the arrangement for the promotion of development, for both, was used the contend and documentary analysis technique, respectively (DELLAGNELO ; SIL­VA, 2005). The approach of social networks has permitted understand that social re­lationships may extend the collective efficiency of the arrangement, and therefore need to develop policies that encourage the legalization of informal companies in ar­rangement, by showing up themselves representative. Thus, the relations estab­ lished in LPA of confections from Agreste of Pernambuco need for more effective mechanisms to broaden the collective efficiency. Therefore, this way as take place has directly benefited only a group of companies that are linked in some way the sup­portive institutions. So we can conclude that the inter-actor relations have limited the collective efficiency of LPA, being stimulated by the institutions in support only to groups of entrepreneurs, even those that produce external relations for all clustered companies

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In last decades, neural networks have been established as a major tool for the identification of nonlinear systems. Among the various types of networks used in identification, one that can be highlighted is the wavelet neural network (WNN). This network combines the characteristics of wavelet multiresolution theory with learning ability and generalization of neural networks usually, providing more accurate models than those ones obtained by traditional networks. An extension of WNN networks is to combine the neuro-fuzzy ANFIS (Adaptive Network Based Fuzzy Inference System) structure with wavelets, leading to generate the Fuzzy Wavelet Neural Network - FWNN structure. This network is very similar to ANFIS networks, with the difference that traditional polynomials present in consequent of this network are replaced by WNN networks. This paper proposes the identification of nonlinear dynamical systems from a network FWNN modified. In the proposed structure, functions only wavelets are used in the consequent. Thus, it is possible to obtain a simplification of the structure, reducing the number of adjustable parameters of the network. To evaluate the performance of network FWNN with this modification, an analysis of network performance is made, verifying advantages, disadvantages and cost effectiveness when compared to other existing FWNN structures in literature. The evaluations are carried out via the identification of two simulated systems traditionally found in the literature and a real nonlinear system, consisting of a nonlinear multi section tank. Finally, the network is used to infer values of temperature and humidity inside of a neonatal incubator. The execution of such analyzes is based on various criteria, like: mean squared error, number of training epochs, number of adjustable parameters, the variation of the mean square error, among others. The results found show the generalization ability of the modified structure, despite the simplification performed

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Following the study of Andrade et al. (2009) on regular square lattices, here we investigate the problem of optimal path cracks (OPC) in Complex Networks. In this problem we associate to each site a determined energy. The optimum path is defined as the one among all possible paths that crosses the system which has the minimum cost, namely the sum of the energies along the path. Once the optimum path is determined, at each step, one blocks its site with highest energy, and then a new optimal path is calculated. This procedure is repeated until there is a set of blocked sites forming a macroscopic fracture which connects the opposite sides of the system. The method is applied to a lattice of size L and the density of removed sites is computed. As observed in the work by Andrade et al. (2009), the fractured system studied here also presents different behaviors depending on the level of disorder, namely weak, moderated and strong disorder intensities. In the regime of weak and moderated disorder, while the density of removed sites in the system does not depend of the size L in the case of regular lattices, in the regime of high disorder the density becomes substantially dependent on L. We did the same type of study for Complex Networks. In this case, each new site is connected with m previous ones. As in the previous work, we observe that the density of removed sites presents a similar behavior. Moreover, a new result is obtained, i.e., we analyze the dependency of the disorder with the attachment parameter m

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The dissertation examines the influence of relationships among actors from Brazilian Tourism Political Network who compose the National Council of Tourism in the drafting of the National Tourism Plans (PNT) - PNTs 2003/2007 and 2007/2010, focusing on two main types of interaction: cooperation and information exchange. Therefore, the study departed from the understanding that the concept of tourism as a human phenomenon is configured as an essential conceptual basis for the development, implementation and analysis of public policies. The application of Network Theory and Social Network Analysis serves as an analytical tool, in addition, the use of concepts of Policy Networks enabled to interpret, in distinct aspects, the social reality of tourism in a more precise and detailed way. The study had a cross-sectional with a longitudinal perspective and case study was adopted, thus enabling to apply the model of social network analysis and qualitative approach. Through the survey conducted, it was found that the drafting process of National Tourism Plans was the result of the interaction of a complex network of actors from public and private initiatives, who compose the National Council of Tourism, and that their power of influence came out simultaneously, but not symmetrically, for both their performance/intervention in the meetings, and the possession of economic and organizational resources. Hence, the establishment of partnerships and information exchanges among the actors were underlying to the PNT drafting process, both in problems perception and insertion in the government agenda, as in making proposals to solve them, thus guiding the construction of large programs and programs contained in both investigated plans.