Research on the Node Importance of a Weighted Network Based on the K-Order Propagation Number Algorithm
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College of Electronic and Optical Engineering & College of Microelectronics, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
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Bell Honors School, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
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Institute of Intelligent Machines, Hefei Institute of Physical Science Chinese Academy of Sciences, Hefei 230031, China
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National and Local Joint Engineering Laboratory of RF Integration and Micro-Assembly Technology, Nanjing 210003, China
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Authors to whom correspondence should be addressed.
Entropy 2020, 22(3), 364; https://doi.org/10.3390/e22030364
Received: 11 February 2020
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Revised: 12 March 2020
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Accepted: 19 March 2020
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Published: 22 March 2020
(This article belongs to the Special Issue Entropic Forces in Complex Systems)
To describe both the global and local characteristics of a network more comprehensively, we propose the weighted K-order propagation number (WKPN) algorithm to extract the disease propagation based on the network topology to evaluate the node importance. Each node is set as the source of infection, and the total number of infected nodes is defined as the K-order propagation number after experiencing the propagation time K. The simulation of the symmetric network with bridge nodes indicated that the WKPN algorithm was more effective for evaluation of the algorithm features. A deliberate attack strategy, which indicated an attack on the network according to the node importance from high to low, was employed to evaluate the WKPN algorithm in real networks. Compared with the other methods tested, the results demonstrate the applicability and advancement that a lower number of nodes, with a higher importance calculated by the K-order propagation number algorithm, has to achieve full damage to the network structure.
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MDPI and ACS Style
Tang, P.; Song, C.; Ding, W.; Ma, J.; Dong, J.; Huang, L. Research on the Node Importance of a Weighted Network Based on the K-Order Propagation Number Algorithm. Entropy 2020, 22, 364. https://doi.org/10.3390/e22030364
AMA Style
Tang P, Song C, Ding W, Ma J, Dong J, Huang L. Research on the Node Importance of a Weighted Network Based on the K-Order Propagation Number Algorithm. Entropy. 2020; 22(3):364. https://doi.org/10.3390/e22030364
Chicago/Turabian StyleTang, Pingchuan, Chuancheng Song, Weiwei Ding, Junkai Ma, Jun Dong, and Liya Huang. 2020. "Research on the Node Importance of a Weighted Network Based on the K-Order Propagation Number Algorithm" Entropy 22, no. 3: 364. https://doi.org/10.3390/e22030364
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