About this project

This project studies the robustness of country-wide railway networks using network science methods. The analysis focuses on the railway networks of Belgium and the Netherlands. The networks are built from GTFS data and modeled as graphs, with stations represented as nodes and rail connections as edges.

Network efficiency and connectivity are used to track performance as stations are progressively removed from the network. Several disruption scenarios are considered. These include random failures and targeted removal strategies based on topological importance, such as node centrality. The impact of each strategy is evaluated by measuring the resulting loss in network performance.

The analysis highlights vulnerable parts of the network and identifies critical stations whose failure has a disproportionate effect on overall functionality. By comparing different disruption scenarios, the project provides insights into structural weaknesses in national railway systems. These insights are relevant for resilience-oriented railway planning, infrastructure prioritization, and risk assessment.

Discover the team behind this project

Praneesh Sharma
Praneesh SharmaAI Student
Data Scientist & AI developer
Published On: 3 February 2026Categories:

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