Rail transit resilience measurement method under extreme weather events
By constructing resilience curves and spatiotemporal weighted regression models under extreme weather events, the problem of missing spatiotemporal dynamic processes in the existing technology for assessing the resilience of rail transit is solved, enabling accurate assessment and emergency response support for rail transit systems under extreme weather conditions.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SOUTH CHINA NORMAL UNIV
- Filing Date
- 2024-06-25
- Publication Date
- 2026-05-19
AI Technical Summary
Existing technologies lack effective modeling and assessment of the spatiotemporal dynamic processes of extreme weather events and the resilience response of rail transit, failing to accurately reflect the performance differences of different rail transit stations under extreme weather conditions, resulting in inaccurate and ineffective responses from assessment and early warning systems.
By preprocessing subway card swiping data and meteorological data, resilience curves under extreme weather events are constructed, the spatiotemporal similarity of each subway station is calculated, stations are classified based on functional type and resilience performance, a spatiotemporal geographic weighted regression model is used for resilience assessment, and stations are clustered by combining autocorrelation function and spectral clustering methods. A spatiotemporal geographic weighted regression model is then constructed for resilience assessment.
It enables accurate assessment of rail transit systems under extreme weather conditions, provides targeted emergency management strategies, improves the disaster prevention and mitigation capabilities of the transportation system and passenger safety, and enhances emergency response capabilities.
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Figure CN118690338B_ABST