Ticket selling early warning method and device, storage medium and server

Abstract

The embodiment of the invention provides a ticket selling early warning method and device, a storage medium and a server. In the technical scheme provided by the embodiment of the invention, a real-time sold data slice and a real-time remaining ticket slice of a current train number are obtained through a ticket selling track retention technology based on a slice technology, and an actual passenger load factor of the current train number is obtained; according to a historical ticketing database, obtaining an optimal passenger load factor of a date corresponding to the current train number; and when the deviation between the actual passenger load factor and the optimal passenger load factor is not within the error interval, abnormal early warning prompt is carried out, so that the railway passenger transport ticket selling organization is sensitive to abnormal trend identification, the real-time sensitivity is improved, and the method does not depend on manpower.

Description

【Technical field】 [0001] The present invention relates to the field of railway passenger tickets, in particular to a ticket pre-warning method, device, storage medium and server. 【Background technique】 [0002] At present, in the sales process of railway tickets, a ticket sales strategy is adopted, which is mainly based on the ticket pre-distribution plan and supplemented by manual monitoring and adjustment during the ticket sales process. Although this ticketing strategy is in line with the development history and actual production status of railways, with the continuous increase of railway operating mileage and the number of trains and the surge in passenger flow, this ticketing strategy can gradually fail to meet the needs of railway ticketing organization development in actual production applications. This is because, on the one hand, the current ticket allocation scheme is highly dependent on passenger flow forecasting. However, as passenger demand is affected by variou...

AI Technical Summary

Problems solved by technology

Although this ticketing strategy is in line with the development history and actual production status of the railway, as the operating mileage of the railway and the number of trains continue to increase, and the passenger flow surges, this ticketing strategy gradually fails to meet the needs of the development of railway ticketing organizations in actual production and application.

Because, on the one hand, the current fare allocation plan is highly dependent on passenger flow forecasting, but because passenger demand is affected by various factors such as competitive traffic modes, weather changes, and emergencies, passenger flow forecasting is uncertain, and the passenger flow forecasting method is very important to the actual situation. There is a certain deviation in the restoration of passenger flow, which inevitably leads to differences between the pre-sale plan formulated before the pre-sale period and the real passenger flow demand during the pre-sale period; Not only is the real-time performance and sensitivity of the abnormal trend identification of ticket sales weak, but it is time-consuming and laborious, and the labor cost is huge. At the same time, there is no clear standard definition for the "abnormal" discrimination in ticket sales, which leads to the need to improve the accuracy of manual monitoring, and It is difficult to quantify and efficiently manage a large number of trains by manual monitoring

[0003] To sum up, there are problems in the current railway passenger ticketing organization, such as insensitivity to abnormal trend identification, weak real-time sensitivity, and strong manual dependence

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