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Goods volume prediction method and device, electronic device and storage medium

A forecasting method and forecasting device technology, applied in the field of logistics, can solve problems such as excessive deviation of forecasted cargo volume data, and achieve the effect of improving efficiency and accuracy

Pending Publication Date: 2020-03-06
DEPPON LOGISTICS
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Problems solved by technology

[0004] In view of this, the purpose of the embodiments of the present application is to provide a cargo volume forecasting method, device, electronic equipment, and storage medium to improve the problem of excessive deviation of forecasted cargo volume data obtained by traditional cargo volume forecasting methods

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  • Goods volume prediction method and device, electronic device and storage medium
  • Goods volume prediction method and device, electronic device and storage medium

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Embodiment Construction

[0029] The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.

[0030] It should be noted that like numerals and letters denote similar items in the following figures, therefore, once an item is defined in one figure, it does not require further definition and explanation in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second" and the like are only used to distinguish descriptions, and cannot be understood as indicating or implying relative importance.

[0031] figure 1 It is a schematic flow chart of a cargo volume forecasting method provided in the embodiment of the present application. The embodiment of the present application provides a cargo volume forecasting method, including:

[0032] Step 110: Obtain the first historical cargo volume data in the first time period and the second historical cargo volum...

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Abstract

The embodiment of the invention provides a goods volume prediction method and device, an electronic device and a storage medium, and the method comprises the steps: obtaining first historical goods volume data in a first time period and second historical goods volume data in a second time period, and the first time period being earlier than the second time period; respectively inputting the firsthistorical goods volume data into a plurality of prediction models to obtain a goods volume data prediction value of a second time period output by each prediction model; determining a target prediction model from the multiple prediction models according to the data prediction value output by each prediction model, and the goods volume data prediction value obtained by the target prediction modelbeing closest to the second historical cargo volume data; and predicting the goods volume data by using the target prediction model. According to the invention, the plurality of models are predicted by using the historical goods volume data in advance, and the target prediction model is selected for goods volume data prediction according to the comparison result of the prediction result and the real historical goods volume data, so that the accuracy of goods volume prediction can be improved to a greater extent.

Description

technical field [0001] The present application relates to the field of logistics, and in particular, relates to a cargo volume forecasting method, device, electronic equipment, and storage medium. Background technique [0002] In recent years, with the rise of e-commerce in the express delivery industry, the business volume has also greatly increased, and cargo volume forecasting is an application of machine learning technology forecasting algorithms in logistics companies. For the management personnel of the transfer station, it is of great significance for the arrangement of personnel and vehicles to know in advance how much cargo is about to depart and arrive at the transfer station. [0003] The traditional method of manually forecasting the volume of goods also has a rough estimate of the volume, but the obtained forecasted volume data has large deviations and cannot be systematized, which will affect the rational allocation of resources by front-line colleagues. Cont...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02G06Q10/08G06N20/00
CPCG06Q30/0202G06Q10/083G06N20/00
Inventor 张海斌李艳涛王在道朱银祥王贻宝王潇吴树海
Owner DEPPON LOGISTICS
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