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Logistics business forecasting method and device, and readable storage medium

A forecasting method and business technology, which is applied in the field of logistics, can solve the problems that the logistics business forecasting method cannot take into account both the effect and efficiency, and the efficiency and effect are not satisfactory, so as to achieve the effect of improving the forecasting effect, improving the accuracy rate, and improving the forecasting efficiency

Active Publication Date: 2021-05-25
ANJI AUTOMOTIVE LOGISTICS +1
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Problems solved by technology

[0008] To sum up, the existing logistics business forecasting methods cannot take into account both effect and efficiency, that is, they are not satisfactory in terms of efficiency and effect

Method used

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  • Logistics business forecasting method and device, and readable storage medium
  • Logistics business forecasting method and device, and readable storage medium
  • Logistics business forecasting method and device, and readable storage medium

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Embodiment Construction

[0041] In the existing logistics business forecasting methods, although the re-learning scheme can improve the performance of the trained model on new data, the performance of the old data is not as good as the previous model, that is, some of the old data will be forgotten. features, the effect is poor; the transfer learning scheme does not require too much new data to train an excellent new model, but there is no process of knowledge accumulation in the model, the new model will still forget the features on the old data, and, Old and new data must be generated in the same business scenario and share some features, which is less effective. Although the model library solution can perform well in both new data distribution and old data distribution, it needs to train a large number of models, which is inefficient. Therefore, the existing logistics business forecasting methods cannot take into account both effect and efficiency.

[0042] The embodiment of the present invention g...

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Abstract

A logistics business prediction method and device, and a readable storage medium, the logistics business prediction device includes: obtaining the first historical data of the logistics business; obtaining a shared parameter, and the shared parameter corresponds to the second historical data of the logistics business The shared parameters in the second prediction model of the logistics business, the second historical data of the logistics business is earlier than the first historical data of the logistics business; based on the first historical data of the logistics business and the shared parameters, using machine learning The algorithm generates a first prediction model, the first prediction model includes: the shared parameters and the task parameters corresponding to the first historical data of the logistics business; based on the first prediction model, the logistics business is predicted and generated forecast result. By applying the above-mentioned scheme, the effect and efficiency of logistics business forecasting can be taken into consideration at the same time.

Description

technical field [0001] The embodiment of the present invention relates to the field of logistics technology, in particular to a method and device for predicting logistics business, and a readable storage medium. Background technique [0002] Forecasting in the field of logistics, machine learning algorithms are increasingly being used. Traditional and classic machine learning algorithms usually only consider an independent problem, and solve a specific task through a model trained by historical data with certain probability distribution characteristics. The current artificial intelligence system, including image recognition, online translation, etc., is mainly completed through offline training and online prediction. This method is based on the assumption that the environment in which the data is located is static and does not change. By learning the static data of a certain period of time, the learned model is used to predict the future. [0003] In reality, data will be ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q10/08G06N20/00
CPCG06Q10/04G06Q10/08
Inventor 金忠孝丁文博
Owner ANJI AUTOMOTIVE LOGISTICS
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