Sales volume forecasting method and a training method, a device and an electronic system of a model thereof

A technology of forecasting model and training method, applied in marketing, commerce, instruments, etc., can solve problems affecting sales and capital turnover, poor accuracy, backlog, etc., achieve objective prediction results, improve sales and capital turnover flexibility Effect

Active Publication Date: 2019-03-22
BEIJING KUANGSHI TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

When the number of products is large, the sales volume predicted by this method is often inaccurate, wh

Method used

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  • Sales volume forecasting method and a training method, a device and an electronic system of a model thereof
  • Sales volume forecasting method and a training method, a device and an electronic system of a model thereof
  • Sales volume forecasting method and a training method, a device and an electronic system of a model thereof

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Embodiment 1

[0030] First, refer to figure 1 An example electronic system 100 for implementing the training method of the sales forecast model, the sales forecast method, the device and the electronic system of the embodiment of the present invention will be described.

[0031] Such as figure 1A schematic structural diagram of an electronic system is shown, the electronic system 100 includes one or more processing devices 102, one or more storage devices 104, input devices 106, output devices 108 and one or more image acquisition devices 110, these components The interconnections are via bus system 112 and / or other forms of connection mechanisms (not shown). It should be noted that figure 1 The components and structures of the electronic system 100 shown are exemplary rather than limiting, and the electronic system may also have other components and structures as required.

[0032] The processing device 102 may be a gateway, or an intelligent terminal, or a device including a central pr...

Embodiment 2

[0039] This embodiment provides a method for training a sales forecast model, which is executed by the processing device in the above electronic system; the processing device may be any device or chip with data processing capabilities. The processing device can independently process the received information, or can be connected with a server to jointly analyze and process the information, and upload the processing results to the cloud.

[0040] The sales forecast model can be used to predict the sales of offline or online stores, supermarkets, bookstores, etc.; figure 2 As shown, the training method of the sales forecast model includes the following steps:

[0041] Step S202, acquiring historical sales data of commodities;

[0042] The historical sales data can be obtained from the store’s commodity sales records, inventory records, accounts, etc.; the historical sales data can usually include commodity attribute information, sales volume, sales price, inventory and other in...

Embodiment 3

[0060] This embodiment provides another training method for a sales forecast model, which is implemented on the basis of the above-mentioned embodiments; in this embodiment, the focus is on describing how to obtain sales features and external features for training a machine learning model, and A specific way of determining training samples and training a machine learning model based on the sales features and external features; the method includes the following steps:

[0061] Step 302, obtaining historical sales data of commodities;

[0062] The historical sales data may be the merchant's original order, order details, inventory quantity, commodity metadata (such as commodity price, shelf life, specification) and the like.

[0063] Step 304, looking for missing data and abnormal data in the historical sales data;

[0064] Among them, the missing data can also be referred to as missing points, which are usually blank data in historical sales data, mostly due to omissions in da...

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Abstract

The invention provides a sales volume forecasting method and a training method, a device and an electronic system of a model thereof. The training method of the sales volume forecasting model comprises the following steps: obtaining historical sales data of commodities; Generating sales characteristics related to the sales volume of the merchandise according to the historical sales data; Acquiringthe external characteristics of the corresponding time period of the historical sales data; External features include at least one of a time attribute, a weather characteristic, and a arrival crowd characteristic; determining The training samples according to the sales characteristics and external characteristics, and inputting the training sample into the preset machine learning model for training until the loss function value of the machine learning model converges, and finishing the training to obtain the sales forecast model. The present invention takes into account the sales characteristics related to the sales volume of commodities and the external characteristics that may affect the sales volume of various commodities, so that the prediction result of the sales volume of commodities is more objective and accurate, and contributes to the improvement of the sales volume and the flexibility of the capital turnover.

Description

technical field [0001] The present invention relates to the technical field of data forecasting, in particular to a sales forecasting method and its model training method, device and electronic system. Background technique [0002] In related technologies, offline retail stores usually purchase and replenish goods by manually predicting the sales of goods; Commodity sales in the future (such as the next day, the next week, etc.), and replenish the commodity inventory based on this. This artificial forecasting method usually only considers the sales situation of the product in recent days, and it is difficult to dig out the long-term law of product sales and the relationship between product sales and other factors (such as weather, holidays, price fluctuations, discounts, etc.). [0003] In order to get rid of the above-mentioned blind manual replenishment method, some merchants have adopted a relatively intelligent method for sales forecasting. For example, the average sal...

Claims

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Application Information

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IPC IPC(8): G06Q30/02G06N20/20
CPCG06Q30/0202
Inventor 楼虎彪樊聪杨越
Owner BEIJING KUANGSHI TECH
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