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Method for identifying and predicting bus passenger flow influence factor based on geographically and temporally weighted regression

A technology of geographic weighting and forecasting methods, applied in forecasting, data processing applications, instruments, etc., can solve problems such as poor forecasting accuracy, time change inclusion method, and lost correlation time change information, so as to improve accuracy and image and readability, and the effect of improving the fitting accuracy

Inactive Publication Date: 2017-08-29
BEIHANG UNIV
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Problems solved by technology

Passenger flow forecasting that considers the temporal non-stationarity and spatial non-stationarity of passenger flow at the same time is a new research idea, but most of the current methods are based on spatial changes and cannot incorporate time changes into the method, so the research results will lose their relevance. Time change information cannot completely characterize the changing characteristics of the relationship between land use and passenger flow, and the prediction accuracy is poor

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  • Method for identifying and predicting bus passenger flow influence factor based on geographically and temporally weighted regression
  • Method for identifying and predicting bus passenger flow influence factor based on geographically and temporally weighted regression
  • Method for identifying and predicting bus passenger flow influence factor based on geographically and temporally weighted regression

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Embodiment

[0054] In order to verify the system performance of a method for identifying and predicting the influencing factors of bus passenger flow based on spatio-temporal geographical weighted regression according to the present invention, the passenger flow of traffic districts in Beijing's Sixth Ring Road in June 2015 was collected for example verification.

[0055] 1) if figure 2 As shown, it is a schematic diagram of the traffic districts within the Sixth Ring Road in Beijing. There are 1377 districts in total, among which there are 1207 traffic districts with bus passenger flow. The case studies the relationship between the hourly passenger flow of the traffic district and the built environment of the district, and the time is selected from 6:00 to 23:00 for a total of 18 hours. The amount of original passenger flow data is 1207×18=21726.

[0056] The built environment data is the basic POI data of Beijing, including 1,355,509 points of interest in Beijing. According to the cl...

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Abstract

The invention discloses a method for identifying and predicting a bus passenger flow influence factor based on geographically and temporally weighted regression (GTWR). The method comprises steps of: extracting a traffic zone hour bus passenger flow and calculating built environment density; 2, constructing a space-time three-dimensional coordinate system according to the time of a passenger flow observation point and latitude and longitude to calculate space-time distance, and reckoning a spatial regression weight matrix according to a Gaussian function and the distance; 3, calculating a relation between a passenger flow volume and land utilization under different space-time conditions based on the GTWR; and 4, obtaining a change of a relevant parameter to a coefficient according to the calculation to perform visualization processing in time and space, and analyzing an inherent law. The method takes account of the influence of a time factor on the bus passenger flow and the built environment relation, can deeply excavate an internal relation between the passenger flow and the land utilization, accurately predicts the bus passenger flow, and provides the scientific theoretical guidance for the bus line planning and operation management.

Description

technical field [0001] The invention belongs to the technical field of intelligent traffic information processing, in particular to a method for identifying and predicting influencing factors of bus passenger flow based on spatiotemporal geographic weighted regression (GTWR). Background technique [0002] With the continuous acceleration of the urbanization process and the popularization of automobiles, the road traffic volume is gradually increasing. A large number of private cars lead to a series of problems such as traffic congestion and environmental pollution. Vigorously developing public transportation is one of the most effective ways to solve urban congestion. The analysis of public transportation demand is the foundation of developing public transportation, and the core content of public transportation demand analysis is to explore the causes of public transportation passenger flow and predict the passenger flow. Fully understanding the influencing factors of pass...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/26
CPCG06Q10/04G06Q50/26
Inventor 马晓磊张继宇丁川于海洋刘剑锋
Owner BEIHANG UNIV
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