Static scheduling method for public bikes based on demand prediction and central radiation network

A technology for public bicycles and demand forecasting, applied in the field of urban traffic management and control

Active Publication Date: 2018-05-15
SOUTHEAST UNIV +1
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  • Abstract
  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

[0003] However, during the peak hours of travel, the phenomenon of "no car to borrow, no pile to return" often occurs

Method used

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  • Static scheduling method for public bikes based on demand prediction and central radiation network
  • Static scheduling method for public bikes based on demand prediction and central radiation network
  • Static scheduling method for public bikes based on demand prediction and central radiation network

Examples

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Comparison scheme
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Embodiment Construction

[0071] The present invention will be further described below in conjunction with embodiment and accompanying drawing. The data selected for this example are 200 public bicycle stations in the downtown area of ​​Nanjing, including a total of 1,425,734 public bicycle IC card swiping records.

[0072] Step 1: Take the factors that affect the borrowing and returning amount of public bicycles as predictors, and use the random forest algorithm to predict the borrowing and returning amount of public bicycles at each site during peak hours. The specific steps are as follows:

[0073] Step 1. Select the initial predictors that affect the amount of public bicycle borrowing and repayment: historical borrowing and repayment amount, temperature, weather conditions, riding distance, riding time, date type, as shown in Table 1 below; and then the initial predictors (X 1 、X 2 、X 3 、X 4 、X 5 、X 6 、X 7 、X 8 、X 9 、X 10 、X 11 ) to sort by importance, as attached figure 2 Shown, and d...

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Abstract

The invention discloses a static scheduling method for public bikes based on demand prediction and a central radiation network. The method comprises the steps of carrying out demand prediction on eachstation by taking the central radiation network as a framework based on existing public bike stations, and finally determining an optimal scheduling path. The method mainly comprises the following steps: (1) analyzing multiple factors which influence the demands of the public bikes, predicting borrowing and returning amounts of each station in rush hours by taking the factors as prediction factors through a random forest (Random Forest, RF for short) algorithm; (2) based on a demand prediction amount of each station, putting forwards a two-stage scheduling strategy for firstly generating a central point and then carrying out scheduling based on the central point, and establishing a central point generation model; (3) solving the central point generation model by virtue of an artificial bee colony algorithm; and (4) establishing a public bike scheduling model based on the generated central point, so as to obtain the optimal scheduling path.

Description

technical field [0001] The invention relates to a public bicycle static dispatching technology based on demand forecasting and a hub-and-spoke network, belonging to the field of urban traffic management and control. Background technique [0002] At present, among the green and environment-friendly means of transportation, subways and buses have undoubtedly become people's first choice, but neither the subway nor the bus can completely solve the terminal transportation problem. After taking the subway and the bus, people still need to walk to the final destination. destination. The emergence of public bicycles not only effectively makes up for this defect, solves the "last mile" problem of the public transportation system, but also realizes the transfer function and solves the node traffic problem, thereby improving the mobility and accessibility of public transportation. [0003] However, during peak hours of travel, the phenomenon of "no car to borrow, no pile to return" o...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/30G06N3/00
CPCG06N3/006G06Q10/047G06Q10/0631G06Q50/30
Inventor 刘志远程龙黄迪陈学武冷军强王彤彦孙健金扬曹莹
Owner SOUTHEAST UNIV
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