Issue |
E3S Web Conf.
Volume 409, 2023
International Conference on Management Science and Engineering Management (ICMSEM 2023)
|
|
---|---|---|
Article Number | 03012 | |
Number of page(s) | 13 | |
Section | Data Science | |
DOI | https://doi.org/10.1051/e3sconf/202340903012 | |
Published online | 01 August 2023 |
Information Entropy-based Edge Importance Identification of Road Network: A Case of Highway in Sichuan Province
1 School of Business, Sichuan University, Chengdu 610065, People’s Republic of China
2 School of Business Administration, University of Haifa, Haifa 3498838, Israel
* e-mail: zengziqiang@scu.edu.cn.
Due to the severe damage and huge loss caused by natural disasters to road networks, the protection of the road network is essential. Edge importance identification can help preserve the road network by protecting key edges. This paper proposes a new network performance measure method and introduces a new edge load redistribution method in cascading failure model. To identify different edge importance in the network, this paper proposes three edge importance evaluation metrics, including information entropy of degree values, information entropy of iterative factors and two-dimensional evaluation metric based on the Pareto non-dominated set which combines two single metrics. A case study of highway road in Sichuan province with 204 nodes and 322 edges which was affected by Luding Earthquake is conducted to demonstrate the best one of the three metrics, including data from the Department of Transport of Sichuan Province. The final results of the chi-square test and Kendall’s correlation coefficient comparing the importance ranking of the three metrics with the ranking derived from the network performance assessment model indicate that the two-dimensional evaluation metrics have the best performance and that the road network tends to collapse at the same time when attacked against the road network under different edge rankings, suggesting that the effect of cascading failures should be limited early.
Key words: Cascading failure / Network performance / Entropy / Information theory / Identification
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.