Logistics service prediction method and device, and readable storage medium

A forecasting method and forecasting device technology, applied in the field of logistics, can solve the problems that the logistics business forecasting method cannot take into account both effect and efficiency, and the efficiency and effect are not satisfactory.

Active Publication Date: 2019-01-15
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

Method used

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  • Logistics service prediction method and device, and readable storage medium
  • Logistics service prediction method and device, and readable storage medium
  • Logistics service prediction 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 method and apparatus for predicting logistics services, a readable storage medium, the predicting apparatus for logistics services comprising: acquiring first historical data of logistics services;acquiring a shared parameter, the shared parameter being a shared parameter in a second prediction model corresponding to a second historical data of a logistics service, the second historical data ofthe logistics service being earlier than the first historical data of the logistics service; generating a first prediction model using a machine learning algorithm based on the first historical dataof the logistics service and the shared parameters, the first prediction model comprising: task parameters corresponding to the shared parameters and the first historical data of the logistics service; predicting a logistics service based on the first prediction model, and generating a prediction result. Applying the above scheme, the effect and efficiency of logistics business forecasting can betaken into account simultaneously.

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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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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