Electric power business collaborative classification method and system based on C4.5 decision tree algorithm

Abstract

The invention discloses an electric power business collaborative classification method and system based on a C4.5 decision tree algorithm, and the method comprises the following steps: obtaining an electric power business collaborative related database, and extracting a sample set S from the electric power business collaborative related database; extracting an index set A, wherein the index set Acontains indexes for evaluating the business collaboration data; calculating the information entropy and the information gain ratio of each index for the sample set S based on a C4.5 algorithm so as to select a proper root node and a proper intermediate node; constructing a decision tree according to the selected root node; evaluating and selecting each service cooperation scheme based on the decision tree. The invention further discloses a corresponding system. According to the invention, the information entropy and the information gain ratio are used for calculation, and classification rulesare easy to understand and high in accuracy. The method is applied to collaborative data calculation and analysis of businesses such as power outsourcing, optimal division features are selected as nodes to generate a decision-making tree and perform data classification, classification is quick and good in effect, and collaborative management of the businesses such as power outsourcing is effectively achieved.

Description

technical field [0001] The present invention relates to the technical field of power system data processing, in particular to a method and system for collaborative classification of power services based on a C4.5 decision tree algorithm. Background technique [0002] With the construction requirements of "Ubiquitous Power Internet of Things", the country continues to accelerate the pace of development and promote the reform of the power system. my country's power supply companies have introduced advanced data technologies such as big data and artificial intelligence to build a world-class energy Internet with global competitiveness. The company's strategic deployment is escorted. [0003] In order to achieve intensive management of human resources, finance, and materials to meet the needs of new forms, power supply companies sometimes need to outsource part of their business to mobilize social resources. However, these business processes may have certain risks in terms of pr...

AI Technical Summary

Problems solved by technology

Therefore, the original sample data is messy. If it cannot be effectively classified and evaluated, and the optimal power collaborative work plan cannot be obtained, it is likely to cause a reduction in work efficiency and benefits

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