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Relevant bibliographies by topics / Watts-strogatz

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Academic literature on the topic 'Watts-strogatz'

Author: Grafiati

Published: 4 June 2021

Last updated: 7 February 2022

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Journal articles on the topic "Watts-strogatz"

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Lahtinen, Jani, János Kertész, and Kimmo Kaski. "Sandpiles on Watts–Strogatz type small-worlds." Physica A: Statistical Mechanics and its Applications 349, no. 3-4 (2005): 535–47. http://dx.doi.org/10.1016/j.physa.2004.10.024.

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Zhou, Xiaobo, and Ying Tan. "Group-decided Watts-Strogatz particle swarm optimisation." International Journal of Computational Science and Engineering 6, no. 1/2 (2011): 52. http://dx.doi.org/10.1504/ijcse.2011.041212.

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DARABOS, CHRISTIAN, MARIO GIACOBINI, and MARCO TOMASSINI. "PERFORMANCE AND ROBUSTNESS OF CELLULAR AUTOMATA COMPUTATION ON IRREGULAR NETWORKS." Advances in Complex Systems 10, supp01 (2007): 85–110. http://dx.doi.org/10.1142/s0219525907001124.

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We investigate the performances of collective task-solving capabilities and the robustness of complex networks of automata using the density and synchronization problems as typical cases. We show by computer simulations that evolved Watts–Strogatz small-world networks have superior performance with respect to several kinds of scale-free graphs. In addition, we show that Watts–Strogatz networks are as robust in the face of random perturbations, both transient and permanent, as configuration scale-free networks, while being widely superior to Barabási–Albert networks. This result differs from information diffusion on scale-free networks, where random faults are highly tolerated by similar topologies.

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NEAL, ZACHARY P. "How small is it? Comparing indices of small worldliness." Network Science 5, no. 1 (2017): 30–44. http://dx.doi.org/10.1017/nws.2017.5.

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AbstractMany studies have attempted to determine whether an observed network exhibits a so-called “small-world structure.” Such determinations have often relied on a conceptual definition of small worldliness proposed by Watts and Strogatz in their seminal 1998 paper, but recently several quantitative indices of network small worldliness have emerged. This paper reviews and compares three such indices—the small-world quotient (Q), a small-world metric (ω), and the small-world index(SWI)—in the canonical Watts–Strogatz re-wiring model and in four real-world networks. These analyses suggest that researchers should avoid Q, and identify considerations that should guide the choice between ω and SWI.

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Liangxun Shuo, Yiying Chen, Wenbin Li, and Zexing Zhang. "Research on Evolution Entropy of Watts-Strogatz Model." Journal of Convergence Information Technology 8, no. 8 (2013): 46–53. http://dx.doi.org/10.4156/jcit.vol8.issue8.6.

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Xia, Yongxiang, Jin Fan, and David Hill. "Cascading failure in Watts–Strogatz small-world networks." Physica A: Statistical Mechanics and its Applications 389, no. 6 (2010): 1281–85. http://dx.doi.org/10.1016/j.physa.2009.11.037.

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Luo, Lunhan, and Jianan Fang. "A Study of How the Watts-Strogatz Model Relates to an Economic System’s Utility." Mathematical Problems in Engineering 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/693743.

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Watts-Strogatz model is a main mechanism to construct the small-world networks. It is widely used in the simulations of small-world featured systems including economic system. Formally, the model contains a parameters set including three variables representing group size, number of neighbors, and rewiring probability. This paper discusses how the parameters set relates to the economic system performance which is utility growth rate. In conclusion, it is found that, regardless of the group size and rewiring probability, 2 to 18 neighbors can help the economic system reach the highest utility growth rate. Furthermore, given the range of neighbors and group size of a Watts-Strogatz model based system, the range of its edges can be calculated too. By examining the containment relationship between that range and the edge number of an actual equal-size economic system, we could know whether the system structure has redundant edges or can achieve the highest utility growth ratio.

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Wang, Er-Shen, Chen Hong, Xu-Hong Zhang, and Ning He. "Cascading failures with coupled map lattices on Watts–Strogatz networks." Physica A: Statistical Mechanics and its Applications 525 (July 2019): 1038–45. http://dx.doi.org/10.1016/j.physa.2019.04.031.

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Wang, Yan, and Xin-Jian Xu. "Quantum transport with long-range steps on Watts–Strogatz networks." International Journal of Modern Physics C 27, no. 02 (2015): 1650015. http://dx.doi.org/10.1142/s0129183116500157.

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We study transport dynamics of quantum systems with long-range steps on the Watts–Strogatz network (WSN) which is generated by rewiring links of the regular ring. First, we probe physical systems modeled by the discrete nonlinear schrödinger (DNLS) equation. Using the localized initial condition, we compute the time-averaged occupation probability of the initial site, which is related to the nonlinearity, the long-range steps and rewiring links. Self-trapping transitions occur at large (small) nonlinear parameters for coupling [Formula: see text] (1), as long-range interactions are intensified. The structure disorder induced by random rewiring, however, has dual effects for [Formula: see text] and inhibits the self-trapping behavior for [Formula: see text]. Second, we investigate continuous-time quantum walks (CTQW) on the regular ring ruled by the discrete linear schrödinger (DLS) equation. It is found that only the presence of the long-range steps does not affect the efficiency of the coherent exciton transport, while only the allowance of random rewiring enhances the partial localization. If both factors are considered simultaneously, localization is greatly strengthened, and the transport becomes worse.

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Herzel, Hanspeter. "How to Quantify 'Small-World Networks'?" Fractals 06, no. 04 (1998): 301–3. http://dx.doi.org/10.1142/s0218348x98000353.

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Recently Watts and Strogatz emphasized the widespread relevance of 'small worlds' and studied numerically networks between complete regularity and complete randomness. In this letter, I derive simple analytical expressions which can reproduce the empirical observations. It is shown how a few random connections can turn a regular network into a 'small-world network' with a short global connection but persisting local clustering.

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Dissertations / Theses on the topic "Watts-strogatz"

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Allen, Andrea J. "Average Shortest Path Length in a Novel Small-World Network." Oberlin College Honors Theses / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=oberlin1516362622694547.

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Books on the topic "Watts-strogatz"

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Coolen, A. C. C., A. Annibale, and E. S. Roberts. Specific constructions. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198709893.003.0009.

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This chapter presents network-generating models which cannot be neatly categorized as growing, nor as defined primarily through a target degree distribution. They are best understood as mechanistic constructions designed to elucidate a particular feature of the network. In the first sub-section, the Watts–Strogatz model is introduced and motivated as a construction to achieve both a high degree of clustering and a low average path length. Geometric graphs, in their Euclidian flavour, are shown to be a natural choice for broadcast networks. The Hyperbolic variant is informally described, because it is known to be a natural space in which to embed hierarchical graphs. Planar graphs have very specific real-world applications, but are extraordinarily challenging to analyze mathematically. Finally, weighted graphs allow for concepts such as traffic to be incorporated into the random graph model.

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Bianconi, Ginestra. Classical Percolation, Generalized Percolation and Cascades. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198753919.003.0012.

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This chapter characterizes the robustness of multiplex and multilayer networks using classical percolation, directed percolation and antagonistic percolation. Classical percolation determines whether a finite fraction of nodes of the multilayer networks are connected by any type of connection. Classical percolation can be affected by multiplexity since the degree correlations among different layers can modulate the robustness of the entire multilayer network. Directed percolation describes the propagation of a disease requiring cooperative infection from different layers of the multiplex network. It displays a rich phase diagram including both continuous and discontinuous phase transitions. Antagonist percolation on a duplex network describes the competition between two layers and can give rise to hysteresis loops corresponding to phases that either one layer or the other can percolate Avalanches generated by the generalized Sandpile Model and Watts–Strogatz Model are also discussed, emphasizing their relevance for studying the stability of power grids and financial systems.

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Coolen, Ton, Alessia Annibale, and Ekaterina Roberts. Generating Random Networks and Graphs. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198709893.001.0001.

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This book supports researchers who need to generate random networks, or who are interested in the theoretical study of random graphs. The coverage includes exponential random graphs (where the targeted probability of each network appearing in the ensemble is specified), growth algorithms (i.e. preferential attachment and the stub-joining configuration model), special constructions (e.g. geometric graphs and Watts Strogatz models) and graphs on structured spaces (e.g. multiplex networks). The presentation aims to be a complete starting point, including details of both theory and implementation, as well as discussions of the main strengths and weaknesses of each approach. It includes extensive references for readers wishing to go further. The material is carefully structured to be accessible to researchers from all disciplines while also containing rigorous mathematical analysis (largely based on the techniques of statistical mechanics) to support those wishing to further develop or implement the theory of random graph generation. This book is aimed at the graduate student or advanced undergraduate. It includes many worked examples, numerical simulations and exercises making it suitable for use in teaching. Explicit pseudocode algorithms are included to make the ideas easy to apply. Datasets are becoming increasingly large and network applications wider and more sophisticated. Testing hypotheses against properly specified control cases (null models) is at the heart of the ‘scientific method’. Knowledge on how to generate controlled and unbiased random graph ensembles is vital for anybody wishing to apply network science in their research.

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Book chapters on the topic "Watts-strogatz"

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Zhu, Zhuanghua. "Particle Swarm Optimization with Watts-Strogatz Model." In Swarm, Evolutionary, and Memetic Computing. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17563-3_59.

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Ray, Soujanya, Kingshuk Chatterjee, Ritaji Majumdar, and Debayan Ganguly. "Voting in Watts-Strogatz Small-World Network." In Advances in Intelligent Systems and Computing. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7834-2_31.

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Yamanishi, Teruya, and Haruhiko Nishimura. "Firing Correlation in Spiking Neurons with Watts–Strogatz Rewiring." In Natural Computing. Springer Japan, 2010. http://dx.doi.org/10.1007/978-4-431-53868-4_41.

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Zhi, Xu, Gao Jun, Shao Jing, and Zhou Yajin. "Associative Memory with Small World Connectivity Built on Watts-Strogatz Model." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11881070_19.

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Nobari, Sadegh, Qiang Qu, Muhammad Muzammal, and Qingshan Jiang. "Renovating Watts and Strogatz Random Graph Generation by a Sequential Approach." In Web Information Systems Engineering – WISE 2018. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02922-7_24.

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Lietz, Haiko. "Watts, Duncan J./Strogatz, Steven H. (1998). Collective Dynamics of » Small- World « Networks. Nature 393, S. 440 – 442." In Schlüsselwerke der Netzwerkforschung. Springer Fachmedien Wiesbaden, 2018. http://dx.doi.org/10.1007/978-3-658-21742-6_130.

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"Watts-Strogatz Local Clustering Coefficient." In Encyclopedia of Systems Biology. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_101627.

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Latora, Vito, and Massimo Marchiori. "The Architecture of Complex Systems." In Nonextensive Entropy. Oxford University Press, 2004. http://dx.doi.org/10.1093/oso/9780195159769.003.0027.

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At the present time, the most commonly accepted definition of a complex system is that of a system containing many interdependent constituents which interact nonlinearly. Therefore, when we want to model a complex system, the first issue has to do with the connectivity properties of its network, the architecture of the wirings between the constituents. In fact, we have recently learned that the network structure can be as important as the nonlinear interactions between elements, and an accurate description of the coupling architecture and a characterization of the structural properties of the network can be of fundamental importance also in understanding the dynamics of the system. In the last few years the research on networks has taken different directions producing rather unexpected and important results. Researchers have: (1) proposed various global variables to describe and characterize the properties of realworld networks and (2) developed different models to simulate the formation and the growth of networks such as the ones found in the real world. The results obtained can be summed up by saying that statistical physics has been able to capture the structure of many diverse systems within a few common frameworks, though these common frameworks are very different from the regular array, or capture the random connectivity, previously used to model the network of a complex system. Here we present a list of some of the global quantities introduced to characterize a network: the characteristic path length L, the clustering coefficient C, the global efficiency E<sub>glob</sub>, the local efficiency E<sub>loc</sub>, the cost Cost, and the degree distribution P(k). We also review two classes of networks proposed: smallworld and scale-free networks. We conclude with a possible application of the nonextensive thermodynamics formalism to describe scale-free networks. Watts and Strogatz [17] have shown that the connection topology of some biological, social, and technological networks is neither completely regular nor completely random. These networks, that are somehow in between regular and random networks, have been named small worlds in analogy with the smallworld phenomenon empirically observed in social systems more than 30 years ago [11, 12].

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Conference papers on the topic "Watts-strogatz"

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Halim, Felix, Yongzheng Wu, and Roland H. C. Yap. "Routing in the Watts and Strogatz Small World Networks Revisited." In 2010 Fourth IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshop (SASOW). IEEE, 2010. http://dx.doi.org/10.1109/sasow.2010.70.

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Freitas, Cristopher G. S., Heitor S. Ramos, Raquel S. Cabral, Osvaldo A. Rosso, and André L. L. Aquino. "Caracterização de topologia de Redes Veiculares baseada em Teoria da Informação." In X Simpósio Brasileiro de Computação Ubíqua e Pervasiva. Sociedade Brasileira de Computação - SBC, 2018. http://dx.doi.org/10.5753/sbcup.2018.3285.

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Redes Veiculares podem ser estudadas utilizando o comportamento individual de cada véıculo em relação ao tempo, caracterizados pelo deslocamento ou velocidade. No entanto, neste trabalho iremos analisar o comportamento do grafo agregado, que descreve a rede em um aspecto global, encapsulando toda a dinâmica dos véıculos durante o intervalo total amostrado, assim, verificando seus aspectos estruturais com quantificadores de Teoria da Informação para mapear esses dados no plano Complexidade-Entropia. Este método foi aplicadoá 17 redes veiculares, variando suas topologias em V2V, V2I e V2V2I, de forma que seus grafos agregados apresentaram uma dinâmica variável entre o comportamento dos modelos Watts-Strogatz e Barabási-Albert.

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