Structural Robustness of Complex Networks: A Survey of A Posteriori Measures [Feature]

Y Lou, L Wang, G Chen - IEEE Circuits and Systems Magazine, 2023 - ieeexplore.ieee.org
Network robustness is critical for various industrial and social networks against malicious
attacks, which has various meanings in different research contexts and here it refers to the …

A convolutional neural network approach to predicting network connectedness robustness

Y Lou, R Wu, J Li, L Wang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
To quantitatively measure the connectedness robustness of a complex network, a sequence
of values that record the remaining connectedness of the network after a sequence of node …

[HTML][HTML] Robustness evaluation method for unmanned aerial vehicle swarms based on complex network theory

W Xiaohong, Y Zhang, W Lizhi, LU Dawei… - Chinese Journal of …, 2020 - Elsevier
Abstract Unmanned Aerial Vehicle (UAV) swarms have been foreseen to play an important
role in military applications in the future, wherein they will be frequently subjected to different …

An adaptive attack model to network controllability

S Li, W Liu, R Wu, J Li - Reliability Engineering & System Safety, 2023 - Elsevier
For the ultimate goal of protecting the network controllability and enhancing the
controllability robustness, one can learn from how a network can be effectively destructed. In …

A framework of hierarchical attacks to network controllability

Y Lou, L Wang, G Chen - … in Nonlinear Science and Numerical Simulation, 2021 - Elsevier
Network controllability robustness reflects how well a networked dynamical system can
maintain its controllability against destructive attacks. This paper investigates the network …

Leveraging Minimum Nodes for Optimum Key Player Identification in Complex Networks: A Deep Reinforcement Learning Strategy with Structured Reward Shaping

L Zeng, C Fan, C Chen - Mathematics, 2023 - mdpi.com
The problem of finding key players in a graph, also known as network dismantling, or
network disintegration, aims to find an optimal removal sequence of nodes (edges …

Disintegrating spatial networks based on region centrality

ZG Wang, Y Deng, Z Wang, J Wu - Chaos: An Interdisciplinary Journal …, 2021 - pubs.aip.org
Finding an optimal strategy at a minimum cost to efficiently disintegrate a harmful network
into isolated components is an important and interesting problem, with applications in …

Octahedral–Tetrahedral Systems [Co(dppmO,O)3]2+[CoX4]2– Showing Slow Magnetic Relaxation with Two Relaxation Modes

C Rajnák, F Varga, J Titiš, J Moncol… - Inorganic …, 2018 - ACS Publications
Three compounds with octahedral–tetrahedral Co (II) moieties of [Co (dppm O, O) 3][CoX4]
type, where X= SCN (1), Cl (2), or I (4) have been synthesized and characterized by the X …

Complex network robustness prediction using attention-augmented CNN

J Huang, R Wu, J Li - Neural Computing and Applications, 2024 - Springer
Assessing the strength of complex networks is crucial for evaluating their functionality and
monitoring system security. Two primary perspectives for measuring network robustness are …

Training set fuzzification based on histogram to increase the performance of a neural network

E Volna, R Jarusek, M Kotyrba, J Zacek - Applied Mathematics and …, 2021 - Elsevier
This article describes a new approach which uses a histogram to fuzzify variables. We used
a linguistic expression to form a training set output vector. The whole fuzzification process of …