Vulnerability analysis of power communication network based on complex network theory


연구 분야: Strategies



학회: 2023 IEEE 3rd International Conference on Information Technology, Big Data and Artificial Intelligence (ICIBA)


초록

Aiming at the problems of insufficient recognition ability and inaccurate recognition results of traditional communication network weak area identification methods, this paper proposes a communication network weak link identification algorithm based on community influence. Firstly, the community structure of the network is discovered by the community discovery algorithm GN algorithm, which can divide the network into multiple communities; secondly, the communication network weakness assessment index is constructed from two aspects of community local influence and community global influence; finally, the method proposed in this paper is verified and analyzed by the actual power communication network. The simulation results show that the weak link identification algorithm of power communication network proposed in this paper has higher discriminability and accuracy compared with traditional methods.


Author Profile
Runze Wu

North China Electric Power University Beijing China

China
Author Profile
Xinmiao Wang

North China Electric Power University Beijing China

China
Author Profile
Jidong Liu

North China Electric Power University Beijing China

China

📄 논문 정보

발행 연도 2023년
인용수 119
출판 국가 China
사이트 IEEE
좋아요 수 0

연관 논문 목록 (106건)