Multiplex Networks

2014 ◽  
pp. 53-72 ◽  
Author(s):  
Kyu-Min Lee ◽  
Jung Yeol Kim ◽  
Sangchul Lee ◽  
K.-I. Goh
Keyword(s):  
Multiplex Networks

EXPLOSIVE SYNCHRONIZATION OF COMBINATIONAL PHASES ON RANDOM MULTIPLEX NETWORKS

2016 ◽  
Vol 6 (2) ◽  
pp. 99-108 ◽  
Author(s):  
Guanying Huo ◽  
Xin Jiang ◽  
Lili Ma ◽  
Quantong Guo ◽  
Yifang Ma ◽  
...  
Keyword(s):  
Multiplex Networks ◽  
Explosive Synchronization

Control of relay synchronization in multiplex networks by time delay

2020 ◽  
Author(s):  
Eckehard Scholl ◽  
Iryna Omelchenko ◽  
Jakub Sawicki
Keyword(s):  
Time Delay ◽  
Multiplex Networks

Social contagions on correlated multiplex networks

2018 ◽  
Vol 499 ◽  
pp. 121-128 ◽  
Author(s):  
Wei Wang ◽  
Meng Cai ◽  
Muhua Zheng
Keyword(s):  
Multiplex Networks

scholarly journals Interlayer adaptation-induced explosive synchronization in multiplex networks

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Anil Kumar ◽  
Sarika Jalan ◽  
Ajay Deep Kachhvah
Keyword(s):  
Multiplex Networks ◽  
Explosive Synchronization

Link prediction in multiplex networks using a novel multiple-attribute decision-making approach

2021 ◽  
pp. 106904
Author(s):  
Hongsheng Luo ◽  
Longjie Li ◽  
Yakun Zhang ◽  
Shiyu Fang ◽  
Xiaoyun Chen
Keyword(s):  
Decision Making ◽  
Link Prediction ◽  
Multiple Attribute Decision Making ◽  
Multiplex Networks ◽  
Multiple Attribute

scholarly journals Spreading of localized attacks on spatial multiplex networks with a community structure

2020 ◽  
Vol 2 (4) ◽  
Author(s):  
Dana Vaknin ◽  
Bnaya Gross ◽  
Sergey V. Buldyrev ◽  
Shlomo Havlin
Keyword(s):  
Community Structure ◽  
Multiplex Networks ◽  
Spatial Multiplex

scholarly journals An information theoretic approach to link prediction in multiplex networks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Seyed Hossein Jafari ◽  
Amir Mahdi Abdolhosseini-Qomi ◽  
Masoud Asadpour ◽  
Maseud Rahgozar ◽  
Naser Yazdani
Keyword(s):  
Real World ◽  
Link Prediction ◽  
Large Scale ◽  
Similarity Measures ◽  
Prediction Method ◽  
General Purpose ◽  
Fast Method ◽  
Theoretic Approach ◽  
Multiplex Networks ◽  
Wide Range

AbstractThe entities of real-world networks are connected via different types of connections (i.e., layers). The task of link prediction in multiplex networks is about finding missing connections based on both intra-layer and inter-layer correlations. Our observations confirm that in a wide range of real-world multiplex networks, from social to biological and technological, a positive correlation exists between connection probability in one layer and similarity in other layers. Accordingly, a similarity-based automatic general-purpose multiplex link prediction method—SimBins—is devised that quantifies the amount of connection uncertainty based on observed inter-layer correlations in a multiplex network. Moreover, SimBins enhances the prediction quality in the target layer by incorporating the effect of link overlap across layers. Applying SimBins to various datasets from diverse domains, our findings indicate that SimBins outperforms the compared methods (both baseline and state-of-the-art methods) in most instances when predicting links. Furthermore, it is discussed that SimBins imposes minor computational overhead to the base similarity measures making it a potentially fast method, suitable for large-scale multiplex networks.

scholarly journals A group-based centrality for undirected multiplex networks: a case study of the Brazilian Car Wash Operation

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Bruno Cesar Barreto De Figueiredo ◽  
Fabiola Guerra Nakamura ◽  
Eduardo Freire Nakamura
Keyword(s):  
Multiplex Networks ◽  
Car Wash
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