Public bicycle peak time demand prediction method considering user reservation data

A technology for public bicycles and demand forecasting, applied in forecasting, data processing applications, instruments, etc., can solve the problems of lag, difficulty in returning a car, and difficulty in borrowing a car, and achieve the effect of improving the accuracy of forecasting

Inactive Publication Date: 2016-06-29
SOUTH CHINA UNIV OF TECH
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Problems solved by technology

It can be found that these dispatches are not based on demand forecasting, and there is a

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  • Public bicycle peak time demand prediction method considering user reservation data
  • Public bicycle peak time demand prediction method considering user reservation data
  • Public bicycle peak time demand prediction method considering user reservation data

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Embodiment Construction

[0051] The present invention will be further described below in conjunction with specific examples.

[0052] like figure 1 Shown, public bicycle peak period demand prediction method of the present invention, comprises the following steps:

[0053] 1) Collect and extract user reservation data during peak hours. According to the mobile phone APP or WeChat official account, the travel plan data of public bicycle users during the peak period of the next day is collected, and relevant data such as the scheduled departure time period, departure point and destination point are extracted.

[0054] 2) Collect usage data of public bicycles during peak hours. According to the historical card swiping records of each outlet, the borrowing data, returning data and corresponding time points of public bicycles during peak hours are extracted.

[0055] 3) Process the reservation data to obtain the reservation demand of different outlets and time periods on the next day. The first step is t...

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Abstract

The invention discloses a public bicycle peak time demand prediction method considering user reservation data. The public bicycle peak time demand prediction method is characterized in that 1) user peak time reservation data can be acquired and extracted; 2) the use data of the public bicycle historical peak time can be acquired; 3) the reservation data can be processed, and the reservation demand quantities of different rental stations at different times in the next day can be acquired; 4) the historical data can be processed, and the demand prediction values of different rental stations at different times in the next day can be acquired; 5) the prediction values can be integrated according to the reservation data and the historical data, and the final borrowing and returning demand quantities of different rental stations at different times can be determined; 6) the scheduling demand table having the time window can be drawn. The public bicycle peak time demand prediction method is advantageous in that the accuracy of predicting the bicycle and locking pile demands of different public bicycle rental stations at peak times can be effectively improved, and the data having the actual reference value can be provided for the peak time scheduling.

Description

technical field [0001] The invention relates to the technical field of domestic urban public bicycle system construction and operation management, in particular to a public bicycle peak demand forecasting method considering user reservation data. Background technique [0002] At present, demand forecasting plays a very important role in the construction and operation management of domestic urban public bicycle systems. In the network planning link of system construction, it is generally necessary to comprehensively consider factors such as regional function types, regional land use properties, service population size, and bicycle use intensity, and use different forecasting methods such as Logit model and transfer volume estimation to estimate the demand for regional public bicycles. Make predictions to determine the layout and scale of public bicycles in the region. Although the results predicted by these methods cannot be said to be very accurate, they can basically meet ...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/30
CPCG06Q10/04G06Q50/30
Inventor 马莹莹叶钦海秦筱然
Owner SOUTH CHINA UNIV OF TECH
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