Identifying node importance based on evidence theory in complex networks
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DOI: 10.1016/j.physa.2019.121538
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Cited by:
- Chen, Sai & Ding, Yueting & Zhang, Yanfang & Zhang, Ming & Nie, Rui, 2022. "Study on the robustness of China's oil import network," Energy, Elsevier, vol. 239(PB).
- Yige Xue & Yong Deng, 2020. "Refined Expected Value Decision Rules under Orthopair Fuzzy Environment," Mathematics, MDPI, vol. 8(3), pages 1-14, March.
- Xiao, Feng & Li, Jin & Wei, Bo, 2022. "Cascading failure analysis and critical node identification in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
- Zhao, Jie & Wang, Yunchuan & Deng, Yong, 2020. "Identifying influential nodes in complex networks from global perspective," Chaos, Solitons & Fractals, Elsevier, vol. 133(C).
- Dong, Chen & Xu, Guiqiong & Meng, Lei & Yang, Pingle, 2022. "CPR-TOPSIS: A novel algorithm for finding influential nodes in complex networks based on communication probability and relative entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
- Chen, Wei & Hou, Xiaoli & Jiang, Manrui & Jiang, Cheng, 2022. "Identifying systemically important financial institutions in complex network: A case study of Chinese stock market," Emerging Markets Review, Elsevier, vol. 50(C).
- Chao Sun & Shiying Li & Yong Deng, 2020. "Determining Weights in Multi-Criteria Decision Making Based on Negation of Probability Distribution under Uncertain Environment," Mathematics, MDPI, vol. 8(2), pages 1-15, February.
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Keywords
Complex networks; Important nodes; Evidence theory; Multi-evidence centrality; Comprehensive measure;All these keywords.
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