KNN algorithm-based electric power material inventory optimization system and method

Abstract

The invention takes a KNN algorithm as the core to realize temporal classification of mass inventory materials in a material storage process of an electric power company according to a power grid material in-stock situation and through dimensions of prefectural and municipal unit, material type, movement type, factory type, warehousing batch number, storage time, unit price, aggregate amount, current date and material warehousing data. Through the classification method provided by the invention, characteristic data classification of electric power material in-stock inventory is realized, material storage time and regions are divided, and normality, expiration and time-limit-exceeding identification of inventory time is effectively achieved.

Description

technical field [0001] The invention relates to the technical fields of electric power production management and material management, in particular to a KNN algorithm classification method for electric power material inventory time. Background technique [0002] At present, the scope of centralized procurement of the State Grid Corporation of China continues to expand, UHV construction is speeding up in an all-round way, safe and reliable power supply capacity and clean energy consumption capacity are rigidly improved, the intensive management of materials should strengthen the whole process management, vigorously promote the standardization of materials, and optimize the procurement strategy. Strengthen information management and control, comprehensively improve the quality of network equipment, and escort the construction of a strong power grid. [0003] However, the relevant information of traditional electric power material inventory management is mainly entered manually...

AI Technical Summary

Problems solved by technology

[0003] However, the relevant information of the traditional power material inventory management is mainly entered manually, and the efficiency of synchronous updating of information is very low in the existing technology, and the manual operation is error-prone

Because logistics and information flow cannot be connected in a timely manner, there is a time difference, resulting in a large backlog of State Grid materials in the warehouse, and there is a waste of State Grid company resources and unreasonable quotas for supporting material reserves.

Images