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Sales volume prediction method and device

A technology of sales volume and forecasting model, applied in the computer field, can solve the problems of sales volume forecast influence, weak stability, not considering environmental factors, etc., to avoid further unsalable sales and accurate sales forecast.

Pending Publication Date: 2019-12-10
BEIJING JINGDONG SHANGKE INFORMATION TECH CO LTD +1
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] (1) Relying on the stability and weak stability of the time series formed by sales data, it is impossible to make predictions for sales data that have not passed the stability or weak stability test
[0005] (2) The influence of environmental factors, such as promotional discounts, seasonality, sales in adjacent areas, etc., on sales forecasts are not considered

Method used

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  • Sales volume prediction method and device

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Embodiment Construction

[0036] Exemplary embodiments of the present invention are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present invention to facilitate understanding, and they should be regarded as exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

[0037] figure 1 is a schematic diagram of main steps of a sales forecast method according to an embodiment of the present invention. Such as figure 1 As shown, the sales forecast method in the embodiment of the present invention mainly includes the following steps:

[0038]Step S101: According to the sales time series corresponding to the product identifier and the time...

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Abstract

The invention discloses a sales volume prediction method and device, and relates to the technical field of computers. One specific embodiment of the method comprises the following steps: determining the number of pre-time periods according to a sales volume time sequence and a time sequence model corresponding to a product identifier; inputting the sales volume time sequence and the environmentaldata of the corresponding time period into a machine learning algorithm to train a sales volume prediction model; and inputting the sales volume data and the environmental data of the front time period number and the environmental data of the next time period into the sales volume prediction model so as to output the sales volume prediction data of the next time period. The method determines the number of pre-time periods based on a time sequence model, and trains a sales volume prediction model based on environmental data to predict sales volume data of a next time period from the sales volume data of the number of pre-time periods. The sales volume prediction model of the method does not depend on the stability of the sales volume time sequence, environmental factors are considered, andsales volume prediction is more accurate.

Description

technical field [0001] The invention relates to the field of computers, in particular to a sales forecast method and device. Background technique [0002] In the process of product sales, sellers need to complete operations such as purchase, stocking, and replenishment of warehouses before actual sales. The data for the above-mentioned various operations of the seller comes from the predicted value of the future rather than the actual value, so it becomes very important to predict the sales volume of the product in the future. At present, the sales forecast of products mainly adopts the moving average method, which predicts the sales data of a future time period based on the sales data of several previous time periods. [0003] In the course of realizing the present invention, the inventor finds that there are at least the following problems in the prior art: [0004] (1) Relying on the stability and weak stability of the time series formed by sales data, it is impossible ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q30/06
CPCG06Q10/06375G06Q30/06
Inventor 裘实张瞻李聚信蒋佳涛
Owner BEIJING JINGDONG SHANGKE INFORMATION TECH CO LTD
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