Abstract: Rumor propagation poses a significant threat to social stability and public order, and controlling its spread can effectively reduce unnecessary panic and misunderstanding. Rumor control is ...

Abstract: Traffic flow prediction is fundamental to traffic information services, control, and guidance. The challenge to accurately model the traffic flow is to comprehensively capture dynamic, ...

Abstract: The increasing penetration of distributed energy resources (DERs) adds variability as well as fast control capabilities to power networks. Dispatching the DERs based on local information to ...

Abstract: In recent years, the construction of behavior-based analysis models is hindered by issues such as insufficient data, difficulty in labeling, and the complexity of behavior types. In reality, ...

Personalized algorithms may quietly sabotage how people learn, nudging them into narrow tunnels of information even when they start with zero prior knowledge. In the study, participants using ...

Dynamic network flow optimisation for evacuation planning focuses on models and algorithms that allocate and route evacuees through a transportation network over time, seeking to minimise total ...

Flow theory explores the assignment and conservation of quantities through the edges of a graph. Classic network‐flow models measure capacities and flows subject to conservation at vertices, ...

Abstract: Measuring river surface velocity is crucial for hydrological monitoring. However, traditional methods exhibit significant limitations under extreme weather conditions and emergency scenarios ...

Abstract: It is crucial to improve the robustness of the IoT against malicious attacks. For scenarios where the network topology is split due to malicious attacks, but can still reconnect fragmented ...

Abstract: To solve the multipath planning with capacity-constrained problems (MPCCP), this paper proposes a solution based on the network flow model, utilizing the network flow-ripple spreading ...