Open AccessKey node mining algorithm for directed weighted air quality network based on propagation characteristics
Author(s) -
Song Chen,
Zhang Xiankun,
Xinqian Liu,
Dawei Ren,
Dong Mei
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1693/1/012066
Subject(s) - key (lock) , node (physics) , computer science , transmission (telecommunications) , data mining , quality (philosophy) , computer network , engineering , telecommunications , computer security , philosophy , structural engineering , epistemology
The decline of air quality seriously affects human life and ecological environment. The blind allocation of governance resources leads to poor improvement. In order to allocate resources reasonably and improve treatment efficiency, a new key nodes mining algorithm for air quality system based on network structure and the characteristics of pollutant transmission is proposed, aiming at resource investing guidance. Firstly, the air quality network is established and its structural characteristics are analyzed. Secondly, according to the diffusion and attenuation mechanism of air pollutants in the network, a bidirectional transmission key node mining algorithm is proposed which takes both the in-links and out-links into consideration. Thirdly, a dynamic independent threshold propagation model in directed weighted network is proposed, and the number of activated nodes is used as evaluation criterion for key node mining results. Finally, experiment is executed on Jing-Jin-Ji PM2.5 air quality network. Experiment results show that the bidirectional transmission key node mining algorithm can get accurate results and good applicability in air quality network.