Distribution network material demand prediction method based on time sequence and hierarchical aggregation

Abstract

The invention relates to a distribution network material demand prediction method based on a time sequence and hierarchical aggregation, and the method comprises the steps: carrying out the step-by-step prediction of a time sequence prediction model and a multi-dimensional hierarchical structure of any to-be-predicted demand material through a hierarchical aggregation method, and continuously completing the demand prediction of all materials. According to the method, a data mining technology is adopted; implementing high feature classification of goods and materials, profiling material demandrules, establishing prediction model, improving material demand prediction capabilities, material purchasing related work of a material department is supported in an auxiliary mode, material requirements of all project types and power supply units are predicted, accumulated to county companies and finally accumulated to the material requirement scale of city companies, normal production of power enterprises is guaranteed, purchasing and inventory cost is saved to a great extent, and enterprise competitiveness is improved; based on accurate prediction of the material demand quantity, the monthly demand quantity prediction error is smaller than 20%, inventory reduction can be achieved in combination with an information tool, and excessive capital occupation caused by too early excessive purchasing is avoided.

Description

technical field [0001] The present invention relates to data processing systems or methods specially suitable for administrative, commercial, financial, management, supervisory or forecasting purposes; processing systems or methods specially suitable for administrative, commercial, financial, management, supervisory or forecasting purposes not included in other categories The technical field of the method, in particular to a method for forecasting distribution network material demand based on time series and hierarchical aggregation. Background technique [0002] At present, with the rapid development of my country's social economy, various functional departments, such as the electric power department, have higher and higher demand for materials, which promotes the prosperity of the power grid engineering market and poses greater challenges to related enterprises. Only by further optimizing enterprise management And all kinds of resource allocation, improve resource utilizati...

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Problems solved by technology

[0006] The present invention solves the problem that in the prior art, the solution is mainly based on big data analysis, resulting in that for different basic data, there may be great differences in prediction results, and it is very difficult to find data loopholes, and the solution error rate is high , low efficiency, and it is not easy to check once a problem occurs. At the same time, it is mainly used to estimate, count, and report by the grassroots units based on experience, and the upper-level professional departments will summarize and review, which also leads to low prediction accuracy and scientificity. Optimized distribution network material demand forecasting method based on time series and hierarchical aggregation

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