A method and device for data prediction based on time series

Abstract

An embodiment of the present application provides a time-series-based data prediction method and device, wherein the method includes: acquiring historical time-series data of multiple category objects, wherein the category objects include one or more data objects ; Select feature category objects from the plurality of category objects, wherein the feature category objects are category objects containing feature data objects, and the feature data objects are data whose life cycle is less than a preset time threshold Object; based on the historical time series data corresponding to the feature category object, predict the target data object from the data objects contained in the feature category object, and the target data object will be generated in the first preset time period in the future A data object whose future time series data satisfy the preset growth trend. According to the principle of time series data, this application can predict the target data objects with explosive power in the near future, so that the prediction results are more consistent with the actual situation and the accuracy rate is higher.

Description

technical field [0001] The present application relates to the technical field of data processing, in particular to a time series-based data prediction method and a time series-based data prediction device. Background technique [0002] With the development of information technology, the layout of rural areas has become a very important aspect of the strategic layout of more and more e-commerce platforms: to let goods go out through e-commerce platforms and to let outside goods enter the countryside. Among rural products, most of them are commodities with high timeliness or seasonal requirements, and even the shelf life is quite short, such as seafood, fresh vegetables and fruits. Such commodities can be called time-sensitive commodities. Time-sensitive commodities refer to commodities with a certain consumption timeliness and a very short shelf life. [0003] In practice, although the demand for time-sensitive commodities is huge, the challenges to e-commerce platforms and ...

AI Technical Summary

Problems solved by technology

[0004] (1) If there are too many warehouses, it will cause excessive logistics pressure, and because of the short shelf life of this type of goods, it is easy to cause huge waste;

[0005] (2) If miscalculation causes insufficient storage, it will cause huge market waste

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