Car rental store site selection method and system based on location data, and readable storage medium

Abstract

The invention discloses a car rental store site selection method and system based on position data and a readable storage medium. The method comprises the steps of collecting related supporting data of car rental store site selection; projecting the collected related matched data to a map of the preliminary planning area, and performing priority setting on the related matched data; and comprehensively calculating the score of the current store address according to the related matching data of different priorities, and determining the site selection of the target store according to the score.

Description

technical field [0001] The invention relates to the field of big data processing, in particular to a location data-based method, system and readable storage medium for car rental stores. Background technique [0002] The existing retail store location selection algorithm is generally based on map big data, mainly through the analysis of population aggregation attributes, consumption attributes, commercial attributes, landmark attributes, etc., to divide hot spots, potential areas, blank areas, etc., and based on this According to their own business needs, determine the selected address. Existing technical algorithms focus on consumption attributes, with the exception of car rental stores. On the one hand, parking resources in cities are relatively tight, and car rental companies have a large number of vehicles to park, so car rental stores The site selection also needs to consider the convenience between the existing parking lot and the convenience of necessary services such...

AI Technical Summary

Problems solved by technology

[0002] The existing retail store location selection algorithm is generally based on map big data, mainly through the analysis of population aggregation attributes, consumption attributes, commercial attributes, landmark attributes, etc., to divide hot spots, potential areas, blank areas, etc., and based on this According to their own business needs, determine the selected address. Existing technical algorithms focus on consumption attributes, with the exception of car rental stores. On the one hand, parking resources in cities are relatively tight, and car rental companies have a large number of vehicles to park, so car rental stores The site selection also needs to consider the convenience between the existing parking lot and the convenience of necessary services such as refueling, maintenance, repair and car washing around the store

On the other hand, high-frequency car rental business scenarios occur in areas such as airports and high-speed rail stations. How to find stores suitable for car rental scenarios in these known areas cannot be covered by the current algorithm.

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