Big data technology-based mining and analysis of application and installation in power business expanding

Abstract

A large amount of data information is generated in the informatization construction of the application and installation in power business expanding of the power system. The traditional data analysis method of the application and installation in power business expanding only establishes a single analysis model for the data, and does not clarify the deep relationship of the data, which leads to the ineffective use of the archival data. For this reason, the mining analysis of the application and installation in power business expanding based on big data technology is proposed. Based on the establishment of the data warehouse of the application and installation in power business expanding, the data of the application and installation in power business expanding are processed by using the combined prediction model. After improving k-means clustering by genetic algorithm, data mining was performed to obtain the relationship between the archive data. The experimental results show that the studied analysis method not only has high data processing efficiency, but also can effectively shorten the application and installation in power business expanding process and improve the economic efficiency of enterprises when applied to actual power operation.