Railway station transfer efficiency optimization method based on DEA-grey correlation weighted method

By using the DEA-grey relational weighted method, a digital twin simulation model of railway stations is constructed, which optimizes the resource allocation and data fusion of railway stations, solves the problem of low transfer efficiency at railway stations, and realizes efficient data analysis and rapid decision support.

CN122221694BActive Publication Date: 2026-07-21LANZHOU JIAOTONG UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
LANZHOU JIAOTONG UNIV
Filing Date
2026-05-15
Publication Date
2026-07-21

AI Technical Summary

Technical Problem

In existing technologies, railway station transfer efficiency suffers from the "three long problems" (long transfer distance, long walking time, and long waiting time) and the isolated storage of multi-source heterogeneous data leads to insufficient information sharing, low tolerance for efficiency value fluctuations, and high prediction error rate, making it difficult to achieve minute-level response and holographic perception.

Method used

A method based on DEA-grey relational weighting is adopted to construct a digital twin simulation model by collecting spatiotemporal fusion data of all dimensions, identify effective and ineffective DMUs, perform projection analysis and optimization, combine the grey relational weighting method to predict future efficiency change trends, generate optimization schemes and verify them through simulation.

Benefits of technology

It achieved a 22% increase in railway station transfer efficiency, a 40% increase in emergency response speed, a 35% increase in passenger satisfaction, reduced resource allocation deviation to below 8%, reduced prediction error rate to below 5%, and shortened decision response time from 8-10 minutes to 90 seconds.

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Abstract

The application discloses a railway station transfer efficiency optimization method based on a DEA-grey correlation weighted method, and relates to the technical field of intelligent traffic management, and comprises the following steps: collecting full-dimension space-time fusion data of a railway station; defining multiple decision units and determining input and output variables based on the full-dimension space-time fusion data; constructing a simulation model and calibrating parameters; determining the efficiency values of the decision units through a DEA model, and then determining effective and ineffective decision units, and performing projection analysis on the ineffective decision units; taking the historical efficiency value sequence of the effective decision units as a reference sequence, taking the historical efficiency value sequence of the ineffective decision units as a comparison sequence, calculating the future efficiency values and change trends of the ineffective decision units through a grey correlation weighted method with a dynamically adjusted resolution coefficient; generating corresponding optimization schemes according to the efficiency evaluation results and the future efficiency change trends; and obtaining optimized decision unit data through simulation model operation simulation. The application can greatly improve the railway station transfer efficiency.
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