Intelligent scheduling method for shared bicycles

Abstract

The invention discloses an intelligent scheduling method for shared bicycles. The method comprises the following steps: step 1, carrying out visual analysis on a shared bicycle user in time and space;Step 2, performing clustering analysis on the stations of each shared bicycle according to the visual analysis result obtained in the step 1; Step 3, constructing a corresponding model according to the clustering analysis result obtained in the step 2, and then predicting the bicycle demand of the shared bicycle station according to the model; And step 4, scheduling the number of bicycles on theshared bicycle station according to the prediction result in the step 3. According to the shared bicycle intelligent scheduling method provided by the invention, through the setting of the step 1, thestep 2, the step 3 and the step 4, the number of bicycles on the shared bicycle station can be effectively analyzed and predicted, and then scheduling is carried out.

Description

Technical field [0001] The invention relates to a scheduling method, and more specifically, to an intelligent scheduling method for shared bicycles. Background technique [0002] With the rapid development of the Internet, the application of mobile Internet technology has received more and more industry attention. In the past two years, the sharing economy or the sharing economy has developed in full swing. Typical representatives of the foreign sharing economy are Uber, Uber and Airbnb. The domestic sharing economy is also developing rapidly. In the field of travel, Internet companies represented by Didi Chuxing, such as Yidao, Shenzhou Zhuhai, and Dida Carpool, have brought great travel convenience to users. However, the above companies still have no business coverage in the field of short-distance travel. In order to better solve the pain point of users in the "last mile" of short-distance travel, a large number of shared bicycle companies have been established. [0003] At ...

AI Technical Summary

Problems solved by technology

[0004] (1) The cost of manual inspection is high and the efficiency is low; the scale of shared bicycles is large and the coverage is wide. It is difficult to solve the problem of no bikes to borrow at other stations for a long time by only relying on manual experience to schedule some fixed stations

[0005] (2) With the gradual increase in the number of outlets, video monitoring cannot understand the situation of each outlet in real time. Therefore, in order to alleviate the problem of difficulty in borrowing and returning cars, improve user satisfaction, and reduce system operating costs, the overall improvement For the service level of the shared bicycle system, reasonable and accurate demand forecasting is necessary. However, the dispatch of the existing shared bicycles is manually dispatched by dispatchers. The overall dispatch process is mainly determined by the dispatcher's own experience. Therefore, The number of shared bicycles at the site cannot be effectively regulated, and it is easy to have problems with borrowing and returning bicycles

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