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
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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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