Results 91 to 100 of about 140,926 (181)

Towards real-world complexity: an introduction to multiplex networks

, 2015
Many real-world complex systems are best modeled by multiplex networks of interacting network layers. The multiplex network study is one of the newest and hottest themes in the statistical physics of complex networks.
Goh, Kwang-Il, Lee, Kyu-Min, Min, Byungjoon   +2 more
core   +1 more source

Sandpiles on multiplex networks

, 2012
We introduce the sandpile model on multiplex networks with more than one type of edge and investigate its scaling and dynamical behaviors. We find that the introduction of multiplexity does not alter the scaling behavior of avalanche dynamics; the system
A. Barrat, A. E. Motter, D. J. Watts, D.-S. Lee, D.-S. Lee, E. Bonabeau, E. J. Lee, H. J. Jensen, I. -M. Kim, J. Um, K. -I. Goh, K.-I. Goh, K.-I. Goh, K.-I. Goh, K.-M. Lee, Kyu-Min Lee, M. E. J. Newman, M. L. Sachtjen, M. Szell, P. Alstrøm, P. Bak, P. Erdős, P. Grassberger, R. Cohen, S. V. Buldyrev   +24 more
core   +1 more source

Interbank markets and multiplex networks: centrality measures and statistical null models

, 2015
The interbank market is considered one of the most important channels of contagion. Its network representation, where banks and claims/obligations are represented by nodes and links (respectively), has received a lot of attention in the recent ...
Bargigli, Leonardo, di Iasio, Giovanni, Infante, Luigi, Lillo, Fabrizio, Pierobon, Federico   +4 more
core   +1 more source

Network robustness of multiplex networks with interlayer degree correlations

, 2014
We study the robustness properties of multiplex networks consisting of multiple layers of distinct types of links, focusing on the role of correlations between degrees of a node in different layers. We use generating function formalism to address various
Goh, K. -I., Lee, Kyu-Min, Min, Byungjoon, Yi, Su Do   +3 more
core   +1 more source

Communication in multiplex transportation networks

Numerical Algorithms
Abstract Complex networks are made up of vertices and edges. The edges, which may be directed or undirected, are equipped with positive weights. Modeling complex systems that consist of different types of objects leads to multilayer networks, in which vertices in distinct layers represent different kinds of ...
Noschese S., Reichel L.
openaire   +2 more sources

Vital node identification based on cycle structure in a multiplex network. [PDF]

Eur Phys J B, 2023
Ye Q, Yan G, Chang W, Luo H.
europepmc   +1 more source

Structural-functional connectivity bandwidth predicts processing speed in mild traumatic brain Injury: A multiplex network analysis. [PDF]

Neuroimage Clin, 2023
Parsons N, Irimia A, Amgalan A, Ugon J, Morgan K, Shelyag S, Hocking A, Poudel G, Caeyenberghs K.   +8 more
europepmc   +1 more source

Correction: Navigating optimal treaty-shopping routes using a multiplex network model. [PDF]

PLoS One, 2022
Park SJ, Lee KM, Yang JS.
europepmc   +1 more source

Navigating optimal treaty-shopping routes using a multiplex network model. [PDF]

PLoS One, 2021
Park SJ, Lee KM, Yang JS.
europepmc   +1 more source

Cycles and clustering in multiplex networks

Physical Review E, 2016
In multiplex networks, cycles cannot be characterized only by their length, as edges may occur in different layers in different combinations. We define a classification of cycles by the number of edges in each layer and the number of switches between layers.
Baxter, Gareth J., Cellai, Davide, Dorogovtsev, Sergey N., Mendes, José F.F.   +3 more
openaire   +4 more sources