Car rental center warehouse item selection method, device, equipment and computer readable storage medium

Abstract

The embodiment of the invention provides a car rental center warehouse item selection method, device and equipment and a computer readable storage medium. The method comprises the steps that feature data of a target city in a first preset historical time period are acquired, wherein the target city is a city provided with at least one car rental center bin, and the feature data are used for representing environment information of all the car rental center bins in the target city and associated data of car types of the target city; according to the feature data, vehicle model demand predictiondata corresponding to each vehicle rental center bin in the target city in a preset time period are obtained through a vehicle model demand prediction model, wherein the vehicle model demand prediction model is obtained by training a decision tree model; and according to the vehicle model demand prediction data, an item selection result of each vehicle rental center bin is determined. According tothe method of the invention, accurate item selection is realized, so that the matching degree between the vehicle parked in the vehicle rental center bin and the demand of the user is high, and the vehicle turnover rate is further improved.

Description

technical field [0001] The embodiments of the present application relate to the field of data processing, and in particular to a method, device, equipment, and computer-readable storage medium for selecting products in a car rental central warehouse. Background technique [0002] With the development of Internet online business, more and more application platforms provide convenience for everyone. Among them, in order to facilitate people's travel, many car rental platforms have been derived. The car rental platform has a central warehouse. Users who need to travel can choose the car model they want to rent through the car rental platform according to their geographical location, and pick up the car at the central warehouse where the vehicle of the selected model is located, so as to realize the travel plan. Since the vehicles in the central warehouse are dynamically sourced from various leasing companies, for the gradual development of the car rental platform, the issue of...

AI Technical Summary

Problems solved by technology

[0004] However, manual statistics require a lot of manual intervention and decision-making based on human experience, and cannot be adjusted in time according to the latest market conditions and changes in user needs, and the popular models in each city are different.

For example, a large proportion of drivers in Hangzhou drive electric vehicles, and electric vehicles are more popular than petrol vehicles; while in Northwest China, due to the imperfect construction of charging piles and the characteristics of sparsely populated areas, people prefer petrol vehicles; then Every time a car rental platform is opened in a new city, it is necessary to investigate the local vehicle conditions and driver preferences in the city, which consumes a lot of manpower for operations

Therefore, the selection of car rental products is affected by many factors, and the existing technology cannot accurately select products, which makes the matching between the vehicles parked in the central warehouse and the needs of users low.

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