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Method for analyzing uncertainty of passenger flow of urban mass transit terminal

A technology of urban rail transit and analysis method, which is applied in the field of passenger flow uncertainty analysis of urban rail transit stations, and can solve problems such as the lack of relevant research on passenger flow of urban rail transit

Active Publication Date: 2014-09-03
SOUTHEAST UNIV
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AI Technical Summary

Problems solved by technology

However, the research objects of these existing achievements are mainly aimed at the uncertainty of road traffic flow, and there is no relevant research on urban rail transit passenger flow.

Method used

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  • Method for analyzing uncertainty of passenger flow of urban mass transit terminal
  • Method for analyzing uncertainty of passenger flow of urban mass transit terminal
  • Method for analyzing uncertainty of passenger flow of urban mass transit terminal

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Embodiment Construction

[0033] The present invention will be further described below in conjunction with specific embodiments.

[0034] Step1. Passenger flow data processing: use the AFC system to obtain the historical transaction data of the station passenger flow, process the original data, set the time interval △T=15 minutes, segment the time according to the time interval △T, and count the traffic in each time period For station passenger flow, an original passenger flow sequence with a time interval of 15 minutes is obtained; urban rail transit operates 17 hours a day (6:00-23:00), so there are 476 station passenger flow data in a week.

[0035] Step2. Establishment of the SARIMA model: The rail transit passenger flow sequence data has a significant weekly cycle characteristic, so the d-order general difference and the D-order seasonal difference with a period of 476 as the step length are performed on the original passenger flow sequence to remove the trend of the sequence and seasonal effects ...

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Abstract

The invention discloses a method for analyzing the uncertainty of the passenger flow of an urban mass transit terminal. The method for analyzing the uncertainty of the passenger flow of the urban mass transit terminal comprises the steps that firstly, sufficient historical passenger flow data are acquired through an AFC system; secondly, the original data are processed, so that a passenger flow sequence with delta T as the time interval is obtained; thirdly, the passenger flow sequence is fitted through an SARIMA model based on the obvious characteristic that the cycle of the passenger flow of the urban mass transit terminal is a week, and the SARIMA model obtained after fitting is taken as a mean equation of a GARCH model; fourthly, a conditional variance equation is established for a residual error sequence of the mean equation, a predicted confidence interval of the GARCH model is obtained through calculation, and the reliability of model prediction is evaluated according to the predicted confidence interval. The method for analyzing the uncertainty of the passenger flow of the urban mass transit terminal can be used for prediction of the short-time passenger flow of the urban mass transit, the credibility, namely the reliability, of the prediction of the short-time passenger flow of the urban mass transit can be improved, and the decision-making support is provided for operation and management of the urban mass transit.

Description

technical field [0001] The invention relates to the intelligent technology of urban rail transit, in particular to a method for analyzing the uncertainty of passenger flow at urban rail transit stations. Background technique [0002] Effective urban rail transit operation and management is an important guarantee for the urban rail transit system to perform its expected functions, and the prediction and analysis of rail transit passenger flow is the basis of rail transit operation management. Accurate and reliable rail transit passenger flow prediction is very important for rail transit operation management. appears to be crucial. The passenger flow of urban rail transit stations is affected by many natural and social factors, and has the remarkable characteristics of nonlinearity and uncertainty. However, the development of urban rail transit in my country is in its early stage, and the research on passenger flow prediction of rail transit has just started. At present, urban...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/30
Inventor 张宁徐世鹏石庄彬钱振东
Owner SOUTHEAST UNIV
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