Method for prediction of shared bike demand quantity based on big data and psychology of users

A bicycle and demand technology, applied in the fields of data statistics and user psychology analysis, shared bicycle planning, and data transmission system, can solve the problems of low utilization rate of shared bicycles and shared bicycles, so as to improve operating income, word-of-mouth image, and prediction effect Accurate and predictable results

Inactive Publication Date: 2018-08-28
SOUTH CHINA UNIV OF TECH
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Problems solved by technology

[0005] The purpose of the present invention is to overcome the shortcomings and deficiencies of the prior art, and propose a method for predicting the demand for shared bicycles based on big data and user psychology. Fitting and prediction based on the vehicle data and the number of reservations, providing users with more humane reservation service, and alleviating the problems of low utilization rate of shared bicycles and difficulty for users to find shared bicycles

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  • Method for prediction of shared bike demand quantity based on big data and psychology of users
  • Method for prediction of shared bike demand quantity based on big data and psychology of users

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Embodiment Construction

[0031] The present invention will be further described below in conjunction with specific examples.

[0032] The specific circumstances of the method for predicting the demand for shared bicycles based on big data and user psychology provided by this embodiment are as follows:

[0033] First, after analyzing the user's psychology, the average walking time acceptable to the user is obtained as T 1 minute.

[0034] After the user arrives at the parking spot, it will take a certain amount of time to select and check the bicycle. According to the actual situation, it will take about T 2 min, this t 2 Minutes can be regarded as the user's "elastic psychology", that is, this T 2 The psychological impact of minutes on users and the T on the way of walking 2 Compared with minutes, its effect is negligible. Therefore, the ideal time-consuming for users to find shared bicycles is (T 1 +T 2 ) minutes, the best range of users radiated by a certain parking point is walking (T 1 +T ...

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Abstract

The present invention discloses a method for prediction of a shared bike demand quantity based on big data and psychology of users. The method concretely comprises the steps of: completing division ofuser radiation ranges of shared bike parking stalls and determination of shared bike putting areas according to users' travel psychology, achieving data analysis of the demand quantity through a mobile phone reservation system, and employing a shared bike demand prediction model and a shared bike demand prediction correction model to combine a big data technology to complete accurate prediction of the demand quantity of the shared bikes of future users in a certain area. The method for prediction of a shared bike demand quantity based on big data and psychology of users increases the usage frequency of the shared bikes, greatly improves the user experience and provides great help for operation revenues of shared bike enterprises.

Description

technical field [0001] The present invention relates to the technical field of shared bicycle planning, data transmission system, data statistics and user psychology analysis, in particular to a method for predicting demand for shared bicycles based on big data and user psychology. Background technique [0002] The shared bicycle service using big data technology refers to the real-time monitoring of the use status and driving track of the shared bicycle through the wireless network, combined with the vehicle's GPS positioning system and the user's mobile phone positioning system, and matches the user with the nearest available shared bicycle and routes. At the same time, it collects information such as the user's usual travel time period, riding frequency, starting and ending points, and single time consumption, and accurately predicts the demand for shared bicycles that will be generated in the future, and then manages and plans shared bicycles. Strategies such as scheduli...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q30/02G06Q30/06
CPCG06Q10/06312G06Q30/0203G06Q30/0645
Inventor 胡郁葱曹睿冲刘彬
Owner SOUTH CHINA UNIV OF TECH
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