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Journal articles on the topic 'Barabási-Albert Model'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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1

BONNEKOH, JOHANNES. "MONTE CARLO SIMULATIONS OF THE ISING AND THE SZNAJD MODEL ON GROWING BARABÁSI–ALBERT NETWORKS." International Journal of Modern Physics C 14, no. 09 (2003): 1231–35. http://dx.doi.org/10.1142/s0129183103005364.

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The Ising model on growing Barabási–Albert networks shows the same ferromagnetic behavior as on static Barabási–Albert networks. Sznajd models on growing Barabási–Albert networks show an hysteresis-like behavior. A nearly full consensus builds up and the winning opinion depends on history. On slow growing Barabási–Albert networks a full consensus builds up. At five opinions in the Sznajd model with limited persuasion on growing Barabási–Albert networks, all odd opinions win and all even opinions loose supporters.

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2

Held, Pascal, Alexander Dockhorn, and Rudolf Kruse. "On Merging and Dividing Social Graphs." Journal of Artificial Intelligence and Soft Computing Research 5, no. 1 (2015): 23–49. http://dx.doi.org/10.1515/jaiscr-2015-0017.

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Abstract Modeling social interaction can be based on graphs. However most models lack the flexibility of including larger changes over time. The Barabási-Albert-model is a generative model which already offers mechanisms for adding nodes. We will extent this by presenting four methods for merging and five for dividing graphs based on the Barabási- Albert-model. Our algorithms were motivated by different real world scenarios and focus on preserving graph properties derived from these scenarios. With little alterations in the parameter estimation those algorithms can be used for other graph mode

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3

LIMA, F. W. S. "SIMULATION OF MAJORITY RULE DISTURBED BY POWER-LAW NOISE ON DIRECTED AND UNDIRECTED BARABÁSI–ALBERT NETWORKS." International Journal of Modern Physics C 19, no. 07 (2008): 1063–67. http://dx.doi.org/10.1142/s0129183108012686.

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On directed and undirected Barabási–Albert networks the Ising model with spin S = 1/2 in the presence of a kind of noise is now studied through Monte Carlo simulations. The noise spectrum P(n) follows a power law, where P(n) is the probability of flipping randomly select n spins at each time step. The noise spectrum P(n) is introduced to mimic the self-organized criticality as a model influence of a complex environment. In this model, different from the square lattice, the order-disorder phase transition of the order parameter is not observed. For directed Barabási–Albert networks the magnetis

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4

LIMA, F. W. S. "ISING MODEL SPIN S = 1 ON DIRECTED BARABÁSI–ALBERT NETWORKS." International Journal of Modern Physics C 17, no. 09 (2006): 1267–72. http://dx.doi.org/10.1142/s0129183106009679.

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On directed Barabási–Albert networks with two and seven neighbours selected by each added site, the Ising model with spin S = 1/2 was seen not to show a spontaneous magnetisation. Instead, the decay time for flipping of the magnetisation followed an Arrhenius law for Metropolis and Glauber algorithms, but for Wolff cluster flipping the magnetisation decayed exponentially with time. On these networks the Ising model spin S = 1 is now studied through Monte Carlo simulations. However, in this model, the order-disorder phase transition is well defined in this system. We have obtained a first-order

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5

Lima, F. Welington S., and J. A. Plascak. "Kinetic Models of Discrete Opinion Dynamics on Directed Barabási–Albert Networks." Entropy 21, no. 10 (2019): 942. http://dx.doi.org/10.3390/e21100942.

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Kinetic models of discrete opinion dynamics are studied on directed Barabási–Albert networks by using extensive Monte Carlo simulations. A continuous phase transition has been found in this system. The critical values of the noise parameter are obtained for several values of the connectivity of these directed networks. In addition, the ratio of the critical exponents of the order parameter and the corresponding susceptibility to the correlation length have also been computed. It is noticed that the kinetic model and the majority-vote model on these directed Barabási–Albert networks are in the

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6

Zhu, Lei, Lei Wang, Xiang Zheng, and Yuzhang Xu. "The Barabási and Albert scale-free network model." Journal of Intelligent & Fuzzy Systems 35, no. 1 (2018): 123–32. http://dx.doi.org/10.3233/jifs-169573.

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7

JACOBMEIER, DIRK. "MULTIDIMENSIONAL CONSENSUS MODEL ON A BARABÁSI–ALBERT NETWORK." International Journal of Modern Physics C 16, no. 04 (2005): 633–46. http://dx.doi.org/10.1142/s0129183105007388.

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A Consensus Model according to Deffuant on a directed Barabási–Albert network was simulated. Agents have opinions on different subjects. A multi-component subject vector was used. The opinions are discrete. The analysis concerns distribution and clusters of agents which are in agreement with the opinions of the subjects. Remarkable results shown that there mostly exists no absolute consensus. It depends on the ratio of number of agents to the number of subjects, whether the communication ends in a consensus or a pluralism. Mostly a second robust cluster remains, in its size depending on the nu

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8

LIMA, F. W. S. "MAJORITY-VOTE ON DIRECTED BARABÁSI–ALBERT NETWORKS." International Journal of Modern Physics C 17, no. 09 (2006): 1257–65. http://dx.doi.org/10.1142/s0129183106008972.

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On directed Barabási–Albert networks with two and seven neighbours selected by each added site, the Ising model was seen not to show a spontaneous magnetisation. Instead, the decay time for flipping of the magnetisation followed an Arrhenius law for Metropolis and Glauber algorithms, but for Wolff cluster flipping the magnetisation decayed exponentially with time. On these networks the Majority-vote model with noise is now studied through Monte Carlo simulations. However, in this model, the order-disorder phase transition of the order parameter is well defined in this system. We calculate the

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9

SCHNEGG, MICHAEL, and DIETRICH STAUFFER. "DYNAMICS OF NETWORKS AND OPINIONS." International Journal of Bifurcation and Chaos 17, no. 07 (2007): 2399–409. http://dx.doi.org/10.1142/s0218127407018476.

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Social relations between people seldom follow regular lattice structures. In the Barabási–Albert model nodes link to the existing network structure with a probability proportional to the number of nodes previously attached. Here, we present an anthropologically motivated interpolation between Erdös–Rényi and Barabási–Albert rules, where people also prefer to help those who helped them in the past and explore some of its properties. The second part of the paper tackles the question how opinions spread through social networks. We restrict our analysis to one end of the spectrum: scale-free netwo

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10

Jordan, Jonathan, and Andrew R. Wade. "Phase Transitions for Random Geometric Preferential Attachment Graphs." Advances in Applied Probability 47, no. 2 (2015): 565–88. http://dx.doi.org/10.1239/aap/1435236988.

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Vertices arrive sequentially in space and are joined to existing vertices at random according to a preferential rule combining degree and spatial proximity. We investigate phase transitions in the resulting graph as the relative strengths of these two components of the attachment rule are varied.Previous work of one of the authors showed that when the geometric component is weak, the limiting degree sequence mimics the standard Barabási-Albert preferential attachment model. We show that at the other extreme, in the case of a sufficiently strong geometric component, the limiting degree sequence

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11

Jordan, Jonathan, and Andrew R. Wade. "Phase Transitions for Random Geometric Preferential Attachment Graphs." Advances in Applied Probability 47, no. 02 (2015): 565–88. http://dx.doi.org/10.1017/s0001867800007989.

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Vertices arrive sequentially in space and are joined to existing vertices at random according to a preferential rule combining degree and spatial proximity. We investigate phase transitions in the resulting graph as the relative strengths of these two components of the attachment rule are varied. Previous work of one of the authors showed that when the geometric component is weak, the limiting degree sequence mimics the standard Barabási-Albert preferential attachment model. We show that at the other extreme, in the case of a sufficiently strong geometric component, the limiting degree sequenc

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12

Abramov, Aleksandr, Uliana Gorik, Andrei Velichko, et al. "Barabási–Albert-Based Network Growth Model to Sustainable Urban Planning." Sustainability 17, no. 3 (2025): 1095. https://doi.org/10.3390/su17031095.

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Urban planning and development require methodologies to address the challenges of managing urban growth. This study uses Vladivostok as a case study to explore urban evolution and apply predictive models for socio-economic development. By analyzing the life cycle of the city and breaking down its growth processes into key components, specific patterns and strategies tailored to Vladivostok’s development are identified. The Barabási–Albert (BA) network growth model is used to study the temporal dynamics of the city’s urban network, enabling forecasts and optimization of its infrastructure, comm

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13

Alencar, David S. M., Tayroni F. A. Alves, Gladstone A. Alves, et al. "Opinion Dynamics Systems on Barabási–Albert Networks: Biswas–Chatterjee–Sen Model." Entropy 25, no. 2 (2023): 183. http://dx.doi.org/10.3390/e25020183.

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A discrete version of opinion dynamics systems, based on the Biswas–Chatterjee–Sen (BChS) model, has been studied on Barabási–Albert networks (BANs). In this model, depending on a pre-defined noise parameter, the mutual affinities can assign either positive or negative values. By employing extensive computer simulations with Monte Carlo algorithms, allied with finite-size scaling hypothesis, second-order phase transitions have been observed. The corresponding critical noise and the usual ratios of the critical exponents have been computed, in the thermodynamic limit, as a function of the avera

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14

Ruiz, Diego, and Jorge Finke. "Lyapunov–based Anomaly Detection in Preferential Attachment Networks." International Journal of Applied Mathematics and Computer Science 29, no. 2 (2019): 363–73. http://dx.doi.org/10.2478/amcs-2019-0027.

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Abstract Network models aim to explain patterns of empirical relationships based on mechanisms that operate under various principles for establishing and removing links. The principle of preferential attachment forms a basis for the well-known Barabási–Albert model, which describes a stochastic preferential attachment process where newly added nodes tend to connect to the more highly connected ones. Previous work has shown that a wide class of such models are able to recreate power law degree distributions. This paper characterizes the cumulative degree distribution of the Barabási–Albert mode

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15

Túri, József. "Some remarks of random graphs." Multidiszciplináris tudományok 11, no. 5 (2021): 251–55. http://dx.doi.org/10.35925/j.multi.2021.5.26.

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At the beginning of the paper, the known models are briefly presented (The Barabási–Albert model, Watts–Strogatz model, Erdős-Rényi model). In the later part of the paper, some results are presented, which are valid in the Erdős-Rényi model and are also related to the dominant sets of graphs. These results will be considered further in a later paper (Bacsó et al., 2021).

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16

Zsuppán, Sándor. "Examples for an extended Barabási-Albert model with random initial degrees." Dimenziók: matematikai közlemények 8 (2020): 3–13. http://dx.doi.org/10.20312/dim.2020.01.

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We develop a Papkovich-Neuber type representation formula for the solutions of the Navier-Lamé equation of linear elastostatics for spatial star-shaped domains. This representation is compared to the existing ones.

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17

LIMA, F. W. S. "MIXED ALGORITHMS IN THE ISING MODEL ON DIRECTED BARABÁSI–ALBERT NETWORKS." International Journal of Modern Physics C 17, no. 06 (2006): 785–93. http://dx.doi.org/10.1142/s0129183106008753.

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On directed Barabási–Albert networks with two and seven neighbours selected by each added site, the Ising model does not seem to show a spontaneous magnetisation. Instead, the decay time for flipping of the magnetisation follows an Arrhenius law for Metropolis and Glauber algorithms, but for Wolff cluster flipping the magnetisation decays exponentially with time. On these networks the magnetisation behaviour of the Ising model, with Glauber, HeatBath, Metropolis, Wolf or Swendsen–Wang algorithm competing against Kawasaki dynamics, is studied by Monte Carlo simulations. We show that the model e

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18

KRAWIECKI, A. "STOCHASTIC RESONANCE IN THE ISING MODEL ON A BARABÁSI–ALBERT NETWORK." International Journal of Modern Physics B 18, no. 12 (2004): 1759–70. http://dx.doi.org/10.1142/s0217979204025026.

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Stochastic resonance is investigated in the Ising model with ferromagnetic coupling on a Barabási–Albert network, subjected to weak periodic magnetic field. Spectral power amplification as a function of temperature shows strong dependence on the number of nodes, which is related to the dependence of the critical temperature for the ferromagnetic phase transition, and on the frequency of the periodic signal. Double maxima of the spectral power amplification evaluated from the time-dependent magnetization are observed for intermediate frequencies of the periodic signal, which are also dependent

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19

ALEKSIEJUK, AGATA. "MICROSCOPIC MODEL FOR THE LOGARITHMIC SIZE EFFECT ON THE CURIE POINT IN BARABÁSI–ALBERT NETWORKS." International Journal of Modern Physics C 13, no. 10 (2002): 1415–18. http://dx.doi.org/10.1142/s012918310200398x.

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We found that numbers of densely connected clusters in Barabási–Albert (BA) networks follow the exponential distribution. Heuristic arguments presented in the paper allow us to deduce that the critical temperature of the Ising model on the BA network is closely related to critical temperature of the largest densely connected cluster within the network. The arguments explain the logarithmic dependence of the critical temperature on the size of the network.

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20

QIN, QIONG, ZHIPING WANG, FANG ZHANG, and PENGYUAN XU. "EVOLVING SCALE-FREE NETWORK MODEL." International Journal of Modern Physics B 22, no. 13 (2008): 2139–49. http://dx.doi.org/10.1142/s0217979208039307.

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The Barabási–Albert (BA) model is extended here to include the concept of modifying the preferential attachment and combining the global preferential attachment with local preferential attachment. Our preferential attachment makes the nodes with higher degree increase less rapidly than the BA model after a long time. The maximum degree is introduced. We compare the time-evolution of the degree of the BA model and our model to illustrate that our model can control the degree of some nodes increasing dramatically with increasing time. Using the continuum theory and the rate equation method, we o

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21

Lima, F. W. S. "Evolution of egoism on semi-directed and undirected Barabási-Albert networks." International Journal of Modern Physics C 26, no. 12 (2015): 1550135. http://dx.doi.org/10.1142/s0129183115501351.

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Through Monte Carlo simulations, we study the evolution of the four strategies: Ethnocentric, altruistic, egoistic and cosmopolitan in one community of individuals. Interactions and reproduction among computational agents are simulated on undirected and semi-directed Barabási–Albert (BA) networks. We study the Hammond–Axelrod (HA) model on undirected and semi-directed BA networks for the asexual reproduction case. With a small modification in the traditional HA model, our simulations showed that egoism wins, differently from other results found in the literature where ethnocentric strategy is

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22

Bianconi, Ginestra. "Mean field solution of the Ising model on a Barabási–Albert network." Physics Letters A 303, no. 2-3 (2002): 166–68. http://dx.doi.org/10.1016/s0375-9601(02)01232-x.

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23

Chassin, David P., and Christian Posse. "Evaluating North American electric grid reliability using the Barabási–Albert network model." Physica A: Statistical Mechanics and its Applications 355, no. 2-4 (2005): 667–77. http://dx.doi.org/10.1016/j.physa.2005.02.051.

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24

Krishnan, Jeyashree, Reza Torabi, Andreas Schuppert, and Edoardo Di Napoli. "A modified Ising model of Barabási–Albert network with gene-type spins." Journal of Mathematical Biology 81, no. 3 (2020): 769–98. http://dx.doi.org/10.1007/s00285-020-01518-6.

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Abstract The central question of systems biology is to understand how individual components of a biological system such as genes or proteins cooperate in emerging phenotypes resulting in the evolution of diseases. As living cells are open systems in quasi-steady state type equilibrium in continuous exchange with their environment, computational techniques that have been successfully applied in statistical thermodynamics to describe phase transitions may provide new insights to the emerging behavior of biological systems. Here we systematically evaluate the translation of computational techniqu

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25

Min, Lin, Wang Gang, and Chen Tian-Lun. "A Modified Earthquake Model Based on Generalized Barabási–Albert Scale-Free Networks." Communications in Theoretical Physics 46, no. 6 (2006): 1011–16. http://dx.doi.org/10.1088/0253-6102/46/6/011.

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26

Moisset de Espanés, Pablo, Ivan Rapaport, Daniel Remenik, Ivan Rapaport, Daniel Remenik, and Javiera Urrutia. "Robust reconstruction of Barabási-Albert networks in the broadcast congested clique model." Networks 67, no. 1 (2015): 82–91. http://dx.doi.org/10.1002/net.21662.

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27

GONZÁLEZ, M. C., A. O. SOUSA, and H. J. HERRMANN. "OPINION FORMATION ON A DETERMINISTIC PSEUDO-FRACTAL NETWORK." International Journal of Modern Physics C 15, no. 01 (2004): 45–57. http://dx.doi.org/10.1142/s0129183104005577.

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The Sznajd model of socio-physics, with only a group of people sharing the same opinion can convince their neighbors, is applied to a scale-free random network modeled by a deterministic graph. We also study a model for elections based on the Sznajd model and the exponent obtained for the distribution of votes during the transient agrees with those obtained for real elections in Brazil and India. Our results are compared to those obtained using a Barabási–Albert scale-free network.

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28

JACOBMEIER, DIRK. "FOCUSING OF OPINIONS IN THE DEFFUANT MODEL: FIRST IMPRESSION COUNTS." International Journal of Modern Physics C 17, no. 12 (2006): 1801–8. http://dx.doi.org/10.1142/s0129183106010108.

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This paper treats the opinion dynamics of an unequal, initial opinion distribution. We simulate the Deffuant model on a directed Barabási–Albert network with discrete opinions and several subjects. We notice a focusing of the the resulting opinion distribution during the simulation towards the average value of the initial opinion distribution. A small change of the focusing is seen. A dependency of this change on the number of subjects and opinions is detected and indicates the change as a consequence of discretization of the opinions. Hereby the average value of the initial opinion distributi

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29

WICHMANN, SØREN, DIETRICH STAUFFER, CHRISTIAN SCHULZE, and ERIC W. HOLMAN. "DO LANGUAGE CHANGE RATES DEPEND ON POPULATION SIZE?" Advances in Complex Systems 11, no. 03 (2008): 357–69. http://dx.doi.org/10.1142/s0219525908001684.

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An earlier study [24] concluded, based on computer simulations and some inferences from empirical data, that languages will change the more slowly the larger the population gets. We replicate this study using a more complete language model for simulations (the Schulze model combined with a Barabási–Albert network) and a richer empirical dataset [12]. Our simulations show either a negligible or a strong dependence of language change on population sizes, depending on the parameter settings; while empirical data, like some of the simulations, show a negligible dependence.

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30

Kuryliak, Yulian, Michael Emmerich, and Dmytro Dosyn. "Study on the Influence of Direct Contact Network Topology on the Speed of Spread of Infectious Diseases in the Covid-19 Case." Vìsnik Nacìonalʹnogo unìversitetu "Lʹvìvsʹka polìtehnìka". Serìâ Ìnformacìjnì sistemi ta merežì 9 (June 10, 2021): 151–66. http://dx.doi.org/10.23939/sisn2021.09.151.

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The management of epidemics received much interest in recent times, due to devastating outbreaks of epidemic diseases such as Ebola and COVID-19. This paper investigates the effect of the structure of the contact network on the dynamics of the epidemic outbreak. In particular we focus on the peak number of critically infected nodes, because this determines the workload of intensive health-care units and should be kept low when managing an epidemic. Simulation of virus propagation in complex networks of different topologies, generated according to the models of Erdős—Rényi, Watts-Strogatz, Bara

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31

STAUFFER, D., and H. MEYER-ORTMANNS. "SIMULATION OF CONSENSUS MODEL OF DEFFUANT et al. ON A BARABÁSI–ALBERT NETWORK." International Journal of Modern Physics C 15, no. 02 (2004): 241–46. http://dx.doi.org/10.1142/s0129183104005644.

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In the consensus model with bounded confidence, studied by Deffuant et al. (2000), two randomly selected people who differ not too much in their opinion both shift their opinions towards each other. Now we restrict this exchange of information to people connected by a scale-free network. As a result, the number of different final opinions (when no complete consensus is formed) is proportional to the number of people.

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LIMA, F. W. S., and GEORG ZAKLAN. "A MULTI-AGENT-BASED APPROACH TO TAX MORALE." International Journal of Modern Physics C 19, no. 12 (2008): 1797–808. http://dx.doi.org/10.1142/s0129183108013357.

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We embed the behavior of tax evasion into the standard two-dimensional Ising model. In the presence of an external magnetic field, the Ising model is able to generate the empirically observed effect of tax morale, i.e., the phenomenon that in some countries tax evasion is either rather high or low. The external magnetic field captures the agents' trust in governmental institutions. We also find that tax authorities may curb tax evasion via appropriate enforcement mechanisms. Our results are robust for the Barabási–Albert and Voronoi–Delaunay networks.

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33

WANG, BING, HUANWEN TANG, ZHONGZHI ZHANG, and ZHILONG XIU. "EVOLVING SCALE-FREE NETWORK MODEL WITH TUNABLE CLUSTERING." International Journal of Modern Physics B 19, no. 26 (2005): 3951–59. http://dx.doi.org/10.1142/s0217979205032437.

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The Barabási–Albert (BA) model is extended to include the concept of local world and the microscopic event of adding edges. With probability p, we add a new node with m edges which preferentially link to the nodes presented in the network; with probability 1-p, we add m edges among the present nodes. A node is preferentially selected by its degree to add an edge randomly among its neighbors. Using the continuum theory and the rate equation method we get the analytical expressions of the power-law degree distribution with exponent γ=3 and the clustering coefficient c(k)~k-1+c. The analytical ex

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Dos Santos, A. M., M. L. De Almeida, G. A. Mendes, and L. R. Da Silva. "Generalized scale-free homophilic network." International Journal of Modern Physics C 26, no. 09 (2015): 1550097. http://dx.doi.org/10.1142/s0129183115500977.

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We propose a simple network growth process where the preferential attachment contains two essential parameters: homophily, namely, the tendency of sites to link with similar ones, and the number of attaching neighbors. It jointly generalizes the Barabási–Albert model and the scale-free homophilic model with a control parameter which tunes the importance of the homophily on preferential attachment process. Our results support a detailed discussion about different kinds of correlation, in special a fitness correlation introduced in this paper, and comparisons between BA model, scale-free homophi

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FELIJAKOWSKI, K., and R. KOSINSKI. "BOUNDED CONFIDENCE MODEL IN COMPLEX NETWORKS." International Journal of Modern Physics C 24, no. 08 (2013): 1350049. http://dx.doi.org/10.1142/s0129183113500496.

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This paper presents a study of the bounded confidence model applied to the complex networks. Two different cases were examined: opinion formation process in the Barabási–Albert network and corruption spreading in a hierarchical network. For both cases, the value of the bounded confidence parameter ε was assumed as a constant, or its value was dependent on the degree of a node in the network. To measure the opinion formation and corruption spreading processes, we introduced the order parameter related to the number of interfaces in the system. As a results of numerical simulations, the influenc

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36

SANTIAGO, ANTONIO, and ROSA M. BENITO. "EVOLUTION OF HETEROGENEOUS NETWORKS UNDER PREFERENTIAL ATTACHMENT." International Journal of Bifurcation and Chaos 20, no. 03 (2010): 923–27. http://dx.doi.org/10.1142/s0218127410026216.

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In this paper, we present results concerning a natural extension of the class of heterogeneous preferential attachment models, a generalization of the Barabási–Albert model to heterogeneous networks. In this extended class, the network nodes enjoy a nonzero attractiveness even when their connectivity degrees are zero. We analytically show that the degree densities of models in the extended class exhibit a richer scaling behavior than their homogeneous counterparts, and that power-law scaling in their degree distribution is robust in the presence of the offset in the attachment kernel.

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WANG, JIAN-WEI, and LI-LI RONG. "CASCADING FAILURES IN BARABÁSI–ALBERT SCALE-FREE NETWORKS WITH A BREAKDOWN PROBABILITY." International Journal of Modern Physics C 20, no. 04 (2009): 585–95. http://dx.doi.org/10.1142/s0129183109013819.

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In this paper, adopting the initial load of a node j to be [Formula: see text], where kj is the degree of the node j and α is a tunable parameter that controls the strength of the initial load of a node, we propose a cascading model with a breakdown probability and explore cascading failures on a typical network, i.e., the Barabási–Albert (BA) network with scale-free property. Assume that a failed node leads only to a redistribution of the load passing through it to its neighboring nodes. According to the simulation results, we find that BA networks reach the strongest robustness level against

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Lachgar, A., and A. Achahbar. "Network growth with preferential attachment and without “rich get richer” mechanism." International Journal of Modern Physics C 27, no. 02 (2015): 1650020. http://dx.doi.org/10.1142/s0129183116500200.

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We propose a simple preferential attachment model of growing network using the complementary probability of Barabási–Albert (BA) model, i.e. [Formula: see text]. In this network, new nodes are preferentially attached to not well connected nodes. Numerical simulations, in perfect agreement with the master equation solution, give an exponential degree distribution. This suggests that the power law degree distribution is a consequence of preferential attachment probability together with “rich get richer” phenomena. We also calculate the average degree of a target node at time t[Formula: see text]

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39

KRAWIECKI, A. "DYNAMICAL PHASE TRANSITION IN THE ISING MODEL ON A SCALE-FREE NETWORK." International Journal of Modern Physics B 19, no. 32 (2005): 4769–76. http://dx.doi.org/10.1142/s0217979205033017.

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Dynamical phase transition in the Ising model on a Barabási–Albert network under the influence of periodic magnetic field is studied using Monte-Carlo simulations. For a wide range of the system sizes N and the field frequencies, approximate phase borders between dynamically ordered and disordered phases are obtained on a plane h (field amplitude) versus T/Tc (temperature normalized to the static critical temperature without external field, Tc∝ ln N). On these borders, second- or first-order transitions occur, for parameter ranges separated by a tricritical point. For all frequencies of the ma

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Katona, Zsolt. "Width of a scale-free tree." Journal of Applied Probability 42, no. 3 (2005): 839–50. http://dx.doi.org/10.1239/jap/1127322031.

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Consider the random graph model of Barabási and Albert, where we add a new vertex in every step and connect it to some old vertices with probabilities proportional to their degrees. If we connect it to only one of the old vertices then this will be a tree. These graphs have been shown to have a power-law degree distribution, the same as that observed in some large real-world networks. We are interested in the width of the tree and we show that it is at the nth step; this also holds for a slight generalization of the model with another constant. We then see how this theoretical result can be ap

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Katona, Zsolt. "Width of a scale-free tree." Journal of Applied Probability 42, no. 03 (2005): 839–50. http://dx.doi.org/10.1017/s0021900200000814.

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Consider the random graph model of Barabási and Albert, where we add a new vertex in every step and connect it to some old vertices with probabilities proportional to their degrees. If we connect it to only one of the old vertices then this will be a tree. These graphs have been shown to have a power-law degree distribution, the same as that observed in some large real-world networks. We are interested in the width of the tree and we show that it is at the nth step; this also holds for a slight generalization of the model with another constant. We then see how this theoretical result can be ap

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Min, Lin, Wang Gang, and Chen Tian-Lun. "Self-organized Criticality in a Modified Evolution Model on Generalized Barabási–Albert Scale-Free Networks." Communications in Theoretical Physics 47, no. 3 (2007): 512–16. http://dx.doi.org/10.1088/0253-6102/47/3/027.

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Lima, F. W. S. "Tax Evasion and Multi-Agent-Based Model on Various Topologies." Reports in Advances of Physical Sciences 01, no. 02 (2017): 1730001. http://dx.doi.org/10.1142/s242494241730001x.

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In this work, we use Monte-Carlo simulations to study the control of the fluctuations for tax evasion in the economics model proposed by [G. Zaklan, F. Westerhoff and D. Stauffer, J. Econ. Interact. Coordination. 4 (2009) 1; G. Zaklam, F.W.S. Lima and F. Westerhofd, Physica A 387 (2008) 5857.] via a nonequilibrium model with two states ([Formula: see text]) and a noise [Formula: see text] proposed for [M. J. Oliveira, J. Stat. Phys. 66 (1992) 273] and known as Majority-Vote model (MVM) and Sánchez–López-Rodríguez model on communities of agents or persons on some topologies as directed and undi

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de ANGELIS, ANDRÉ FRANCESCHI, GONZALO TRAVIESO, CARLOS ANTÔNIO RUGGIERO, and LUCIANO da FONTOURA COSTA. "ON THE EFFECTS OF GEOGRAPHICAL CONSTRAINTS ON TASK EXECUTION IN COMPLEX NETWORKS." International Journal of Modern Physics C 19, no. 06 (2008): 847–53. http://dx.doi.org/10.1142/s0129183108012546.

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In the present work, the effects of spatial constraints on the efficiency of task execution in systems underlain by geographical complex networks are investigated, where the probability of connection decreases with the distance between the nodes. The investigation considers several configurations of the parameters defining the network connectivity, and the Barabási–Albert network model is also considered for comparisons. The results show that the effect of connectivity is significant only for shorter tasks, the locality of connections implied by the spatial constraints reduces efficiency, and

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QIANG, WEI, GUANGDAO HU, and PENGDA ZHAO. "PHASE TRANSITION IN THE ISING MODEL ON LOCAL-WORLD EVOLVING NETWORKS." International Journal of Modern Physics C 19, no. 11 (2008): 1717–26. http://dx.doi.org/10.1142/s0129183108013242.

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We study the critical behavior of the Ising model on the local-world evolving network. Monte Carlo simulations with the standard Metropolis local update algorithms are performed extensively on the network with different parameters. Ising spins put onto network vertices exhibit an effective phase transition from ferromagnetism to paramagnetism upon heating. The critical temperature has been demonstrated to increase linearly with the average degree of the network as TC ~ 〈k〉. Simulation results on local-world evolving networks with various parameters show logarithmical relationships of the criti

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Gao, Hui, and Zhixian Yang. "A Novel Wireless Sensor Network Evolution Model Based on Energy-Efficiency." International Journal of Online Engineering (iJOE) 13, no. 03 (2017): 4. http://dx.doi.org/10.3991/ijoe.v13i03.6855.

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<span style="font-family: 'Times New Roman',serif; font-size: 12pt; mso-fareast-font-family: SimSun; mso-fareast-theme-font: minor-fareast; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;">The Barabási–Albert (BA) model is a famous complex network model that generates scale-free networks. Wireless sensor networks (WSNs) had been thought to be approximately scale-free through lots of empirical research. Based on the BA model, we propose an evolution model for WSNs. According to actual influence factors such as the remainder energy of each sensor and physic

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Kallakunta, Suneela, and Alluri Sreenivas. "Optimizing Wireless Sensor Networks by Identifying Key Nodes Using Centrality Measures." Momona Ethiopian Journal of Science 16, no. 2 (2024): 289–95. http://dx.doi.org/10.4314/mejs.v16i2.7.

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This study underscores the critical role of graph theory in optimizing the functionality of Wireless Sensor Networks (WSNs). Our research aims to enhance network efficiency by utilizing a variety of centrality metrics, including degree, betweenness, closeness, eigenvector, Katz, PageRank, subgraph, harmonic, and percolation centrality, to identify pivotal nodes. Employing an extended Barabási-Albert model graph of a 50-node network, our methodology focuses on pinpointing nodes crucial for optimal data processing, monitoring, and analysis in WSNs. This comprehensive approach deepens our underst

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Xiao, Zhongdong, Guanghui Zhou, and Ben Wang. "Using modified Barabási and Albert model to study the complex logistic network in eco-industrial systems." International Journal of Production Economics 140, no. 1 (2012): 295–304. http://dx.doi.org/10.1016/j.ijpe.2012.01.033.

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SANTIAGO, ANTONIO, and ROSA M. BENITO. "IMPROVED CLUSTERING THROUGH HETEROGENEITY IN PREFERENTIAL ATTACHMENT NETWORKS." International Journal of Bifurcation and Chaos 19, no. 03 (2009): 1029–36. http://dx.doi.org/10.1142/s0218127409023445.

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In this paper we present a study of the influence of heterogeneity on the clustering of preferential attachment networks. The study is performed by the numerical analysis of the threshold preferential attachment model, a generalization of the Barabási—Albert model to heterogeneous complex networks. Heterogeneous networks are characterized by the existence of intrinsic properties of the nodes which induce specific affinities in their interactions. We analyze the influence of the affinity parameters on the distribution of degree-averaged clustering coefficients of the threshold model. We show th

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FORTUNATO, SANTO. "THE KRAUSE–HEGSELMANN CONSENSUS MODEL WITH DISCRETE OPINIONS." International Journal of Modern Physics C 15, no. 07 (2004): 1021–29. http://dx.doi.org/10.1142/s0129183104006479.

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The consensus model of Krause and Hegselmann can be naturally extended to the case in which opinions are integer instead of real numbers. Our algorithm is much faster than the original version and thus more suitable for applications. For the case of a society in which everybody can talk to everybody else, we find that the chance to reach consensus is much higher as compared to other models; if the number of possible opinions Q≤7, in fact, consensus is always reached, which might explain the stability of political coalitions with more than three or four parties. For Q>7 the number S of survi

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