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A Comprehensive Survey on Community Detection With Deep Learning

Xing Su, Shan Xue, Fanzhen Liu, Jia Wu et al. • IEEE Transactions on Neural Networks and Learning Systems (2022)

Detecting a community in a network is a matter of discerning the distinct features and connections of a group of members that are different from those in other communities. The ability to do this is of great significance in network analysis...

OPENALEX Open Access DOI: https://doi.org/10.1109/tnnls.2021.3137396

A multi-branch network for cooperative spectrum sensing via attention-based and CNN feature fusion

Doi Thi Lan, Quan T. Ngo, Luong Vuong Nguyen, O-Joun Lee • Scientific Reports (2026)

Abstract In cognitive radio (CR) systems, the accurate detection of spectrum holes is a cornerstone for efficient spectrum utilization. However, the increasing complexity of CR environments, particularly those with multiple primary users (P...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-36031-1

Static voltage stability margin prediction considering new energy uncertainty based on graph attention networks and long short‐term memory networks

Tong Liu, Xueping Gu, Shaoyan Li, Yansong Bai et al. • IET Renewable Power Generation (2023)

Abstract The existing static voltage stability margin evaluation methods cannot meet the actual demand of current power grid well in terms of calculation speed and accuracy. Thus, this paper proposes a static voltage stability margin predic...

DOAJ Open Access (DOAJ) DOI: 10.1049/rpg2.12731