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Subway station safety assessment method and device, server and storage medium

A technology for safety assessment and subway stations, which is applied in the field of rail transit, can solve problems such as distortion of evaluation results, high requirements for target data, and reduced evaluation efficiency, achieving the effect of improving accuracy

Pending Publication Date: 2021-02-26
SHENZHEN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Among them, the probabilistic risk assessment method has high requirements for the target data, and the relevant data of the subway station is difficult to collect
The fuzzy comprehensive evaluation method uses expert experience and knowledge to perform fuzzy evaluation on indicators, but ignores the problem of distortion of evaluation results that may be caused by incomplete information on some indicators.
The RBF neural network analysis method requires a certain number of training, testing and learning samples, but in view of the differences in the subway management level of each city, it is difficult to collect samples
The calculation of WSR-D-S evidence theory method is complicated, which reduces the evaluation efficiency

Method used

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  • Subway station safety assessment method and device, server and storage medium
  • Subway station safety assessment method and device, server and storage medium
  • Subway station safety assessment method and device, server and storage medium

Examples

Experimental program
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Embodiment 1

[0048]figure 1 This is a schematic flow chart of a safety assessment method for a subway station provided in the first embodiment of the present invention, and this embodiment can be applied to the safety assessment of a subway station. Such asfigure 1 As shown, the subway station safety assessment method provided in the first embodiment of the present invention includes:

[0049]S110. Obtain evaluation index data of the subway station.

[0050]Specifically, evaluation indicators refer to items that have an impact on the safety performance of subway stations. In this embodiment, the evaluation indicators of subway stations are classified, including 6 first-level indicators and 20 second-level indicators, as shown in Table 1. . In this embodiment, the evaluation index data is the data of each secondary index of the subway station, and the evaluation index data is mostly qualitative data.

[0051]Table 1 Details of evaluation index data

[0052]

[0053]S120: Transform the evaluation index data thro...

Embodiment 2

[0063]figure 2 This is a schematic flow chart of a safety assessment method for a subway station provided in the second embodiment of the present invention. This embodiment is a further refinement of the above-mentioned embodiment. Such asfigure 2 As shown, the subway station safety assessment method provided in the second embodiment of the present invention includes:

[0064]S201. Obtain evaluation index data of the subway station.

[0065]Specifically, refer to Table 1 for evaluation index data.

[0066]S202: Perform a pairwise comparison of the evaluation index data according to the triangular fuzzy language variable to obtain quantitative index data.

[0067]In this embodiment, the quantitative index data is obtained by experts quantifying the index data according to the triangular fuzzy language variables. The triangular fuzzy language variables are shown in Table 2. According to Table 2, compare the evaluation index data in pairs to determine the qualitative relationship between the two (...

Embodiment 3

[0120]image 3 This is a schematic structural diagram of a subway station safety assessment device provided in the third embodiment of the present invention. This embodiment can be applied to the safety assessment of subway stations. The subway station safety assessment device provided in this embodiment can implement the subway station safety assessment method provided in any embodiment of the present invention, and has the corresponding functional structure and beneficial effects of the implementation method. For the content not described in detail in this embodiment, please refer to the present invention. Description of method embodiments.

[0121]Such asimage 3 As shown, the subway station safety evaluation device provided in the third embodiment of the present invention includes: an index data acquisition module 310, a fuzzy judgment matrix building module 320, a maximum weight determination module 330, a gray clustering module 340, and a safety evaluation module 350, in which:

[012...

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Abstract

The embodiment of the invention discloses a subway station safety assessment method and device, a server and a storage medium. The method comprises the steps of obtaining assessment index data of a subway station; converting the evaluation index data through a triangular fuzzy language variable, and constructing a fuzzy judgment matrix; determining the maximum value of index weight data based on the fuzzy judgment matrix; determining a gray clustering evaluation matrix based on the maximum value of the index weight data; and performing safety evaluation on the subway station based on the grayclustering evaluation matrix. According to the embodiment of the invention, the method and device reduces the impact on the subway safety evaluation from the fuzzy evaluation index, iron out the defect that the grey clustering just considers the grey property of the index, and improve the precision of subway station safety evaluation.

Description

Technical field[0001]The embodiments of the present invention relate to the technical field of rail transit, and in particular to a method, device, server and storage medium for safety assessment of subway stations.Background technique[0002]The subway is an important part of the urban transportation network, which plays an important role in alleviating the pressure of urban transportation and provides a strong driving force for urban development. As the scale of the subway network continues to expand, subway passenger traffic is also increasing day by day, which indicates that the safety performance requirements for subway stations are getting higher and higher.[0003]At present, the safety assessment methods for subway stations mainly include probabilistic risk evaluation method, fuzzy comprehensive evaluation method, RBF (Radical Basis Function) neural network analysis method, entropy weight matter element method, WSR-D-S evidence theory method, etc. Among them, the probabilistic r...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q50/30G06K9/62
CPCG06Q10/0635G06Q10/06393G06F18/23G06F18/24G06Q50/40
Inventor 李政道甄宇苏栋刘炳胜肖冰谭颖恩张丽梅
Owner SHENZHEN UNIV
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