Method and device for predicting price of commodity on autonomous vehicle
A technology for autonomous driving and commodity prices, applied in market forecasting, product evaluation, data processing applications, etc., can solve problems such as poor pricing effect, low degree of automation, and reduced pricing efficiency, and achieve the effect of improving pricing effect and pricing efficiency.
Inactive Publication Date: 2022-05-10
NEOLIX TECH CO LTD
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[0004] In view of this, the embodiments of the present disclosure provide a price prediction method and device based on commodities on self-driving vehicles to solve the problems in the prior art that the degree of automation of price prediction for commodities in self-driving vehicles is low and the pricing The effect is relatively poor and the pricing efficiency is reduced
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[0018] In the following description, for the purpose of illustration rather than limitation, specific details such as specific system structures and techniques are presented for a thorough understanding of the embodiments of the present disclosure. It will be apparent, however, to one skilled in the art that the present disclosure may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present disclosure with unnecessary detail.
[0019] As mentioned above, unmanned vehicles, also known as self-driving vehicles, unmanned vehicles or wheeled mobile robots, are integrated and intelligent new era technologies that integrate environmental perception, path planning, state recognition and vehicle control. product. With the rapid development of unmanned driving technology, the application scenarios and scope of self-dri...
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The invention provides a price prediction method and device for commodities on an automatic driving vehicle. The method is applied to an automatic driving vehicle or an unmanned vehicle, and comprises the steps that historical business data are acquired, a multiple linear regression model is constructed, dependent variables of the multiple linear regression model comprise commodity sales volume, independent variables of the multiple linear regression model comprise commodity price, weather information and exposure number, and the exposure number of the multiple linear regression model is calculated; a plurality of parameter values in the multiple linear regression model are obtained based on historical business data; based on the future exposure number and the future weather information, calculating a linear corresponding relation between the future commodity sales volume and the future commodity price in the multiple linear regression model; obtaining a quadratic function corresponding relation between the total revenue of the future commodity and the price of the future commodity based on the linear corresponding relation; and obtaining the value of the future commodity price when the total revenue of the future commodity is the maximum value based on the quadratic function corresponding relation. The accuracy of price prediction can be improved, and the pricing effect is improved.
Description
technical field [0001] The present disclosure relates to the field of unmanned driving technology, and in particular to a method and device for predicting prices of commodities on an automatic driving vehicle. Background technique [0002] Unmanned vehicles, also known as self-driving vehicles, unmanned vehicles. With the development of unmanned driving technology, the application of autonomous vehicles in different industries is becoming more and more widespread. Sweeper etc. [0003] At present, when using an unmanned retail vehicle for commodity sales, it is necessary to predict the price of the commodity in the unmanned retail vehicle, so as to price the commodity reasonably. When the existing technology predicts the pricing of commodities in unmanned retail vehicles, it usually adopts manual pricing strategies or pricing based on estimated sales volume. However, manual pricing strategies rely on human experience and require personnel to manually adjust the pricing of ...
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IPC IPC(8): G06Q30/02G06Q50/30
CPCG06Q30/0201G06Q30/0206G06Q30/0278G06Q50/40
Inventor 李俊宁侯承劭
Owner NEOLIX TECH CO LTD