A learning convolutional neural network approach for network robustness prediction
Network robustness is critical for various societal and industrial networks against malicious
attacks. In particular, connectivity robustness and controllability robustness reflect how well a …
attacks. In particular, connectivity robustness and controllability robustness reflect how well a …
A convolutional neural network approach to predicting network connectedness robustness
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 …
of values that record the remaining connectedness of the network after a sequence of node …
Classification-based prediction of network connectivity robustness
Today, there is an increasing concern about malicious attacks on various networks in society
and industry, against which the network robustness is critical. Network connectivity …
and industry, against which the network robustness is critical. Network connectivity …
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 …
controllability robustness, one can learn from how a network can be effectively destructed. In …
Mis-and disinformation in a bounded confidence model
The bounded confidence model has been widely used to formally study groups of agents
who are sharing opinions with those in their epistemic neighborhood. We revisit the model …
who are sharing opinions with those in their epistemic neighborhood. We revisit the model …
Knowledge-based prediction of network controllability robustness
Network controllability robustness (CR) reflects how well a networked system can maintain
its controllability against destructive attacks. Its measure is quantified by a sequence of …
its controllability against destructive attacks. Its measure is quantified by a sequence of …
Towards optimal robustness of network controllability: An empirical necessary condition
To better understand the correlation between network topological features and the
robustness of network controllability in a general setting, this paper suggests a practical …
robustness of network controllability in a general setting, this paper suggests a practical …
Collective effect of self-learning and social learning on language dynamics: a naming game approach in social networks
Linguistic rules form the cornerstone of human communication, enabling people to
understand and interact with one another effectively. However, there are always irregular …
understand and interact with one another effectively. However, there are always irregular …
Network effects in a bounded confidence model
The bounded confidence model has become a popular tool for studying communities of
epistemically interacting agents. The model makes the idealizing assumption that all agents …
epistemically interacting agents. The model makes the idealizing assumption that all agents …
A framework of hierarchical attacks to network controllability
Network controllability robustness reflects how well a networked dynamical system can
maintain its controllability against destructive attacks. This paper investigates the network …
maintain its controllability against destructive attacks. This paper investigates the network …