Travel equipment price adjustment method, system and equipment based on time period and storage medium

Abstract

The invention provides a travel equipment price adjustment method, system and equipment based on time periods and a storage medium, and the method comprises the steps of obtaining a hot spot use scenethrough the historical data of travel equipment, and enabling the hot spot use scene to be at least limited by a region range and the time periods; based on a preset first price adjustment period, adjusting the use price of the use parameters of the travel equipment in the hotspot use scene according to the first preset parameters; and based on a preset second price adjustment period, at least collecting change parameters of the travel equipment in the hotspot usage scenario after the previous price adjustment, and adjusting the usage price according to the second preset parameters, the period duration of the first price adjustment period being greater than the period duration of the second price adjustment period. According to the invention, the single riding price of the bicycle can beautomatically and dynamically adjusted through the dynamic identification of the supply and demand relationship, so that the overall total business amount of the operation sharing travel equipment isimproved.

Description

Technical field [0001] The present invention relates to the field of big data processing, and in particular to a method, system, equipment and storage medium for adjusting the price of travel equipment based on time period. Background technique [0002] With the continuous development of the shared bicycle and moped industry, bicycles and mopeds are spread all over the country, and the vehicles reach the million and tens of millions level. However, how to price the bicycle riding price has become a problem. Setting a fixed value for all cities in the traditional way creates a "one size fits all" problem. Unable to adjust in accordance with the relationship between supply and demand, unable to maximize the company's profits. For the above problems, proactively predict which business areas are popular locations at different times. The price of vehicles within this range is increased. [0003] In the operation of shared travel equipment, a lot of manpower and capacity are invested ...

AI Technical Summary

Problems solved by technology

However, these locations are constantly changing at different times, and after price adjustments, the relationship between supply and demand will also change, and popular spots may no longer be popular.

It is difficult to match the user's usage habits with pure artificial unified pricing, and it is easy to miss the profit opportunities in hot spots where cars are frequently used, and it is also unable to bear the variable operating costs

[0004] Shared travel equipment cannot simply rely on free and low prices to operate. How to avoid artificial mechanical pricing models is a difficult point in this field, and it is also a very critical technical issue in the pricing and payment process of operating shared travel equipment. It is the lifeblood of the development of the industry, but There is currently no good solution

[0005] Moreover, occasionally shared travel equipment is parked in an unpopular area, leaving it unused, and the cost of sending someone to carry it alone is high, which will easily cause the shared travel equipment to be forced to idle, reducing the overall operating efficiency and efficiency of the shared travel equipment. income

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